Simulation and Optimization

In the patient care chain, medicines are essential items and play a critical role in patient recovery. Inefficient inventory management leads to drug shortages, lack of continuity of drug inventory, reduced patient safety, poor performance, distribution defects, and technological errors, which lead to drug shortages in hospital pharmacies. Providing an efficient approach can minimize costs in the supply chain.
Methods: This study presented a simulation-optimization model for pharmacy inventory management. A training-learning-based optimization algorithm was used to solve the model. The model was programmed and solved in MATLAB software.
Results: Given that the initial inventory is assumed to be zero, the drug price is lower at the beginning of the year, and the number of patients is lower than in the summer. Therefore, the volume of orders is high at the start of the year. The model adjusts the level of orders so that the costs are minimal. As the disease re-emerges and the number of patients increases, demand increases in the ninth and tenth months, and the volume of orders increases again. As demand decreases at the end of the year, the volume of orders also decreases.
Conclusion: By implementing the model during the planning period, while minimizing system costs, the inventory level for all drug categories will be at the desired level, and no inventory shortages will occur.

There are many pieces of research considering slip phenomenon in centrifugal compressors to drive equations for prediction of the slip factor. Inevitably, some simplifications have been imposed on the flow field characteristics and effects of many parameters have been neglected. In this research slip phenomenon is investigated experimentally and numerically in one centrifugal compressor with complex blade curves and splitter blades considering the main effective parameters. Three-dimensional simulation of the compressor viscus flow field with suitable turbulence method was performed using CFD methods. Experimental work was carried out at several rotational speeds and mass flow rates which enabled slip factor results of the compressor as well as, approving accuracy of the simulation results. Effect of main parameters such as rotational speed, mass flow rate, blade number, blade exit angle, diffuser design and tip clearance on slip phenomenon were studied. It was observed that slip fa...

Photovoltaic (PV) systems encounter substantial losses throughout their lifespan due to the different derating factors of PV modules. Those factors mainly vary according to the geographical location and PV panel characteristics. However, the available literature does not explicitly concentrate on the technical and economic impact of the derating factors within the PV system. Owing to that necessity, this study performs a comprehensive analysis of various PV loss parameters followed by a techno-economic assessment of derating factors using the average value on a grid-connected and optimally tilted PV system located in Hatiya, Bangladesh. Some criteria linked to the derating factors such as PV degradation and ambient temperature are further explored to analyze their impact on the aforementioned power system. Simulation results show that PV power generation would vary around 12% annually, subject to a 10% variation in the derating factor. Again, a 10% difference in the derating factor changes the net present cost (NPC) by around 3% to 4%. The system provides the best technical performance concerning annual PV production, power trade with the grid, and the renewable fraction at a higher value of the derating factor since it represents a lower impact of the loss parameters. Similarly, the financial performance in terms of the NPC, levelized cost of energy (LCOE), and grid power exchange cost is found to be lower when the derating factor value is higher.

Photovoltaic (PV) systems encounter substantial losses throughout their lifespan due to the different derating factors of PV modules. Those factors mainly vary according to the geographical location and PV panel characteristics. However, the available literature does not explicitly concentrate on the technical and economic impact of the derating factors within the PV system. Owing to that necessity, this study performs a comprehensive analysis of various PV loss parameters followed by a techno-economic assessment of derating factors using the average value on a grid-connected and optimally tilted PV system located in Hatiya, Bangladesh. Some criteria linked to the derating factors such as PV degradation and ambient temperature are further explored to analyze their impact on the aforementioned power system. Simulation results show that PV power generation would vary around 12% annually, subject to a 10% variation in the derating factor. Again, a 10% difference in the derating factor ...

Following a rise in population, load demand is increasing even in the remote areas and islands of Bangladesh. Being an island that is also far from the mainland of Bangladesh, St. Martin’s is in need of electricity. As it has ample renewable energy resources, a renewable energy-based microgrid system seems to be the ultimate solution, considering the ever-increasing price of diesel fuel. This study proposes a microgrid system and tests its technical and economic feasibility in that area. All possible configurations have been simulated to try and find the optimal system for the island, which would be eco-friendly and economical with and without considering renewable energy options. The existing power supply configuration has also been compared to the best system after analyzing and investigating all technical and economic feasibility. Sensitivity and risk analysis between different cases provide added value to this study. The results show that the current diesel-based system is not v...

An air compressor is the core component of the air supply system of a hydrogen fuel cell, which demands high efficiency and reliable stability in a wide operation region. In this work, a centrifugal air compressor for a hydrogen fuel cell is first designed and then measured experimentally. Furthermore, a test rig for assessing the aerodynamic performance of the centrifugal air compressor is established, which includes a pipeline, gas flowmeter, flow regulating valve, pressure transmitter, centrifugal compressor, controller, DC power supply and computer. Then, the orthogonal method is employed to conduct the aerodynamic performance optimization. Four optimization parameters—including blade number, blade angle at the inlet, blade angle at the outlet and wrap angle—are set with three levels. Nine compressor individuals are designed according to the orthogonal method, and then numerical simulation is implemented to confirm the aerodynamic performance and flow pattern. Results show that ...

In this study, the scale and strategic importance of ERP systems is identified and the problem of ERP implementation is defined. The paper offers a framework for managers which provides the basis for developing an ERP implementation strategy. The case analysis identifies different approaches to ERP implementation, highlights the critical role of legacy systems in influencing the implementation process, and identifies the importance of business process change and software configuration in addition to factors already cited in the literature such as top management support and communication.

The present work aims to carry out an off-design turbocharger modelling powered by exhaust gases from a Wärtsilä 20V34SG engine. First of all, 1-D engine model was already developed in GT-Power software while considering a thermodynamic turbocharger modelling with constant isentropic efficiencies. Secondly, by using the results from 1-D engine model, the off-design turbocharger modelling is calibrated separately in EES software, taking into account compressible assumption, triangle velocities and geometric dimensions. The case study is derived from a R&D project (ANEEL PD-06483-0318/2018) that targets to cool and dehumidify the intake air at compressor's upstream through a cooling coil, thereby allowing engine's operation at reduced knocking conditions. The brake mean effective pressure (BMEP) is varied in the range of 20 to 23.45 bar, corresponding to brake power from 8.7 to 10.2 MW, respectively. With the off-design turbocharger modelling it is possible to analyze its operational behavior under higher BMEP, hence, allowing to predict some important parameters. The results showed that the turbocharger is operating within the manufacturer's limit for BMEP of 23.45 bar, presenting total-to-static isentropic efficiencies of 0.81 and 0.784 for compressor and turbine, respectively, rotational speed around 28135 RPM, pressure ratio at compressor of 4.567 and maintaining control on waste-gate valve.

There are many pieces of research about driving equations for prediction of the slip factor in centrifugal compressors. Inevitably, some simplifications have been imposed by them on the flow field characteristics and effects of many parameters have been neglected. In this research slip phenomenon is investigated experimentally and numerically in a specific centrifugal compressor with complex blade curves and splitter blades considering the main effective parameters like number of blades, exit angle, etc. Threedimensional simulation of the compressor viscus flow field with suitable turbulence method is performed. Experimental work is carried out at several rotational speeds and mass flow rates slip factor. Effects of main parameters such as rotational speed, mass flow rate, blade number, blade exit angle, diffuser design and tip clearance on slip phenomenon are studied. A variation of performance parameters such as pressure ratio and isentropic efficiency with slip factor are investigated, as well. It is observed that slip factor increases, as rotational speed and flow rate increase. Also changing the blade number from 6 to 9 in constant rotational speed and mass flow rate, causes 27 percent increase in slip factor.

In this research, multi-level optimization of the pro le of the splitter blades of a turbocharger compressor is performed using genetic algorithm in order to improve its performance. Successive corrections of the pro le at hub, mid-span, and shroud of the splitter blades, with the objective of decreasing the incidence losses at the leading edge and adjustment of the blade loading at the shroud, result in an impeller having improved splitter blades. The impeller ow eld analysis shows that the optimization has been successful in reducing the ow leakage at the shroud region as well as the losses in the leading edge region. Although numerical simulations predict a decrease by 0.5% in pressure ratio at design point, a 2.2-point improvement in isentropic e ciency is calculated. Based on the optimization results, a new impeller is designed, manufactured, and tested on a turbocharger test bed. Experimental results support the simulation predictions on the expected improvement in performance.

A computationally inexpensive linked ANN-optimization model for planning of groundwater development for agricultural usage is presented and illustrated on a canal command area in India. The planning ensures optimization of zonal crop areas subject to the constraints on maximum groundwater table depth and stream-aquifer interflow under dynamic equilibrium. The data required for developing the ANN models of the envisaged state variables comprise an array of zonal crop areas and the corresponding state variables. These data are generated invoking a pre-calibrated simulation model of groundwater flow.

Groundwater development in canal areas, apart from providing subsurface drainage, helps in enhancing the crop areas since the canal supplies are rarely adequate to meet the complete irrigation demands. Sustainability of this crop area enhancement and the associated groundwater development is linked to the requirement of restricting the resulting state variables viz. long-term water table depths and the stream-aquifer interflows within prescribed limits. In the present study, a simulation model is proposed to address this planning problem. The model accepts the crop areas and several other features of the hydro-agronomic system as inputs and computes the maximum water table depth and the streamaquifer interflows at critical times at the dynamic equilibrium. Under the dynamic equilibrium the excess of annual withdrawals over the annual vertical recharge is compensated by lateral inflows from hydraulically connected drains. As such the total annual inflow and outflow balance each other and the annual time series of head becomes stationary. Therefore dynamic equilibrium represents the annual scenario corresponding to an indefinite sustenance of the cropping/pumping pattern. The proposed strategy is illustrated by applying it to the command of Eastern Yamuna canal system (India) that is experiencing a severe water deficit. Simulation runs are conducted for three cropping patterns representing current scenario, ambitious and conservative patterns.

This work aims to present an industrial perspective on Catalytic Wet Peroxide Oxidation (CWPO) technology. Herein, process simulation and experimental design have been coupled to study the optimal process conditions to ensure high-performance oxidation, minimum H2O2 consumption and maximum energetic efficiency in an industrial scale CWPO unit. The CWPO of phenol in the presence of carbon black catalysts was studied as a model process in the Aspen Plus® v11 simulator. The kinetic model implemented, based on 30 kinetic equations with 11 organic compounds and H2O2 involvement, was valid to describe the complex reaction network and to reproduce the experimental results. The computer experiments were designed on a six-factor Doehlert Matrix in order to describe the influence of the operating conditions (i.e., the different process temperatures, inlet chemical oxygen demands, doses of H2O2 and space time) on each selected output response (conversion, efficiency of H2O2 consumption and ene...

Over the past few years, water allocation problem has increasingly spotlighted by governments, researchers and practitioners. As water plays an important role in people's life and business environment, the problem of water allocation should be considered carefully to properly satisfy demand of water consumers. In the real world applications, problems like water allocation are uncertain owing to long-term planning horizon of such problems. Therefore, employing efficient methods for tackling uncertainty of parameters should be regarded by field researchers. In this regard, this paper proposes a bi-objective mathematical programming model for water distribution network design. The extended model maximizes total profit of water distribution as well as maximizing priority of water transferring among water customer zones. Then, to cope effectively with uncertainty of parameters, a novel robust possibilistic programming method is applied. Then, fuzzy and robust fuzzy programming models are compared against each other and output results confirm superiority and effective performance of the robust fuzzy model in the water allocation problem. Also, output results of the extended model show its accurate performance that results in applicability of the model as a strong planning tool in real world cases.

A computationally inexpensive linked ANN-optimization model for planning of groundwater development for agricultural usage is presented and illustrated on a canal command area in India. The planning ensures optimization of zonal crop areas subject to the constraints on maximum groundwater table depth and stream-aquifer interflow under dynamic equilibrium. The data required for developing the ANN models of the envisaged state variables comprise an array of zonal crop areas and the corresponding state variables. These data are generated invoking a pre-calibrated simulation model of groundwater flow.

This article addresses the challenges of scheduling patients with stochastic service times and heterogeneous service sequences in multi-stage facilities, while considering the availability and compatibility of resources with presence of a variety of patient types. The proposed method departs from existing literature by optimizing the scheduling of patients by integrating mathematical programming, simulation, and multiobjective tabu search methods to achieve our bi-objectives of minimizing the waiting time of patients and the completion time of the facility. Through intensive testing, the performance of the proposed approach is analyzed in terms of the solution quality and computation time, and is compared with the performance of the well-known method, Non-Dominated Sorting Genetic Algorithm (NSGA-II). The proposed method is then applied to actual data of a case study operating department in a major Canadian hospital and promising results have been observed. Based on this study, insights are provided for practitioners.

This paper is concerned the flow simulation and performance analysis of the Centrifugal Compressor Using CFD-Tool. The complex internal flow of centrifugal compressor can be well analyzed, and the unique design system needs to be developed. It should be early to use the interface and also flexible for input and output. A 3-D flow simulation of turbulent-fluid flow is presented to visualize the flow pattern in-terms of velocity, streamline and pressure distribution on the blade surface are graphically interpreted. The standard K-e turbulence model and the simple model algorithm were chosen for turbulence model and pressure distribution well determined. The simulation was steady Heat transfer and moving reference frame was used to consider the impeller interaction under high resolution. Furthermore, A computational Fluid Dynamics (CFD) 3-D simulation is done to analyze the impeller head and efficiency required of centrifugal compressor. The impeller is rotated for a constant revolution and mass flow rate, in this study initially the geometry of centrifugal compressor impeller is created by an ANSYS Vista CCD, and the Blade modeller done by Bladegen, Finally, CFD analysis was performed in ANSYS CFX using the ANSYS Turbo grid meshing tool. According to the analysis, as the number of impeller blades increases, so does the value of the head and power imparted, as well as the impeller's efficiency.

Designing a production process normally is involved with some important constraints such as uncertainty, trade-off between production costs and quality, customer's expectations and production tolerances. In this paper, a novel multi-objective robust optimization model is introduced to investigate the best levels of design variables. The primary objective is to minimize the production cost while increasing robustness and performance. The response surface methodology is utilized as a common approximation model to fit the relationship between responses and design variables in the worst-case scenario of uncertainties. The target mean ratio is applied to ensure the quality of the process by providing the robustness for all types of quality characteristics and with a trade-off between variability and deviance from the ideal point. The Lp metric method is used to integrate all objectives in one overall function. In order to estimate target value of the quality loss by considering production tolerances, the process capability ratio () is applied. At the end, a numerical chemical mixture problem is served to show the applicability of the proposed method.

A computationally inexpensive linked ANN-optimization model for planning of groundwater development for agricultural usage is presented and illustrated on a canal command area in India. The planning ensures optimization of zonal crop areas subject to the constraints on maximum groundwater table depth and stream-aquifer interflow under dynamic equilibrium. The data required for developing the ANN models of the envisaged state variables comprise an array of zonal crop areas and the corresponding state variables. These data are generated invoking a pre-calibrated simulation model of groundwater flow.

This paper presents optimal operating conditions for the post-combustion CO 2 capture process utilizing aqueous amine solutions obtained using a process simulator (HYSYS). Three alkanolamine solutions (Methyldiethanolamine MDEA, DiEthanolAmine DEA and MDEA-DEA mixture) are considered to study the performance of the capture process. The design problem addressed in this paper requires specifying the optimal operating conditions (inlet and outlet temperature of the lean solution stream on the absorber, CO 2 loading, amine composition and flow rates, among others) to achieve the given CO 2 emission targets at a minimum total annual cost. A detailed objective function including total operating costs and investment is considered. The influence of the variation of CO 2 reduction targets and the mixing proportion of amines on the total annual cost is analyzed in detail. Numerical results are presented and discussed using different case studies. The results demonstrate that process simulators can be used as a powerful tool not only to simulate but also to optimize the most important design parameters of the post-combustion CO 2 capture process.

This paper demonstrates the use of models for development of optimal groundwater extraction strategies for an area in which the availability of water from other sources is anticipated by the end of the planning period. The study area: (1) has more wells than can be modeled individually, (2) has an existing piezometric surface that is stressed and not at steady state, and (3) is a portion of a larger aquifer system, the flow regime of which should not be disrupted. As a result, presented models incorporate, respectively: (1) cell-influence coefficients, instead of well-influence coefficients, (2) a convolution equation not previously demonstrated in optimizing groundwater mining, and (3) constant-head/restrained flux boundary condtions. Optimal 10-year groundwater extraction volumes are presented for the intensively irrigated 4700 km 2 Arkansas Grand Prairie. For the assumed conditions, strategies that maximize extraction volume are very similar to those that maximize the present value of net economic return resulting from agricultural production. The sensitivity of results to limits on drawdown and changes in pumping with time is demonstrated.

The study aims to develop an information-computing complex for computer design of a centrifugal compressor with parallel calculation of stages and optimization of the geometric parameters of the impellers and the diffusers. The paper presents a universal methodology and computerized information system of the main geometry parameter determination and optimization of the centrifugal compressor impellers and vanned diffusers. Optimization of cross-sectional areas of the input and output channels of the impeller and diffuser blade channels is held using a gradient descent method by gas flowrate quadratic integral deviation criteria. The information-computing complex is built on the algorithm proposed by the authors and implemented as a computer program with a human-machine interface. Calculation data are written in the form of numerical arrays with the possibility of interpolating data and obtaining graphical dependencies.

A centrifugal compressor, with backward swept impeller, was designed for industrial applications and its performance was evaluated through numerical simulations. The baseline impeller geometry was then modified at the inducer leading edge to impart different forward and back sweeps. The inducer sweep was also associated with lean in the tangential direction. In all, seven impeller configurations were investigated, with inducer leading edge sweep varying from +25° (back sweep) to -20° (forward sweep). CFD simulations have indicated that the pressure ratio at design mass flow rate remained mostly unaffected by sweep, but showed a tendency to increase beyond an inducer back sweep of 20°. Similarly, a forward sweep of 20° gave lowest stall flow rate (highest stall margin). However, with an increase in tip clearance, the impeller with inlet forward sweep of 20° showed an increase in choke and stall mass flow rates. It is concluded that a forward sweep of 20°, with baseline tip clearance ...

The extension and application of a queuing network model to the management of core logistic processes at the Gioia Tauro marine container terminal is presented. Real features incorporated in the model require simulation to solve it. A manager-friendly simulator is designed for the real case study, under the constraint of guaranteeing a finer representation of: the congestion phenomenon at the port channel; the port admission policy for newly arrived vessels in the roadstead; the management of berthing slots; the assignment of cranes for discharge/loading operations. The application software is presented through a detailed discussion of its features, as these appear on panel for system definition and analysis. The simulator computes point and interval estimates for system performance measures. Statistical computations are based upon the issue of batching elementary observations either within the same run or across multiple runs. Simulation experiments are presented and discussed with the aim of recommending a cost-effective method for interval estimates in quantitative scenario analysis.

In this paper a constraint programming (CP) approach for calculating release dates for lots within a supply chain environment is investigated. The lot start times are verified by a simulation model using different dispatching rules focusing on tardiness. To test the presented CP approach a simple fab model is constructed. The fab model consists of parallel batch machines as well as work centers and single machines. The investigated objectives are tardiness, earliness and cycle time. Due to the high complexity decomposition methods for the CP approach are tested. The results from the CP method are lot start dates which are verified by a downstream simulation run. The results show that the presented CP approach could outperform the simulation for all objectives. The content of this paper could be used as a first investigation for new scheduling methods within a supply chain management.

In this paper, a metamodel based hybrid algorithm was developed for optimization of digital computer simulation models. The simulation models are considered to be computationally expensive. It is also considered to have a single stochastic and unconstrained response function. The hybrid algorithm is developed by modification and integration of several concepts and routines. We employed the nested portioning and the particle swarm optimization algori-thms to develop an efficient search mechanism for the hybrid algorithm. Then we integrated the modified Kriging metamodel to the search mechanism for facilitating the function fitting processes of the simulation’s output. The efficiency of the developed hybrid algorithm was then evaluated through computational experiments. Ten complex test problems were selected from the literatures and the efficiency of the developed hybrid algorithm was evaluated by comparing its performances against three known algorithm which are cited in the literat...

The embedding optimization modeling approach is adapted to aid sustainable groundwater quantity and quality management of complex nonlinear multilayer aquifers. Implicit block-centered finite difference approximations of the quasi three-dimensional unsteady flow equation and Galerkin finite element approximations of the two-dimensional advection-dispersion transport equation are embedded directly as constraints in the model. Also used are nonlinear constraints describing river-aquifer interflow, evapotranspiration, and vertical flow reduction due to unconfinement. These circumvent use of large numbers of integer variables. The use of both linear and nonlinear formulations in a cyclical manner reduces execution time and improves confidence in solution optimality. The methodology is demonstrated for Salt Lake valley where groundwater quantity and quality management are needed, the proportion of pumping cells and cells needing head constraint is large, and many flows are described by discrete nonlinear or piecewise linear functions. 1. Introduction Many computer models have been developed for optimizing groundwater management. These have been developed for a wide range of problems and specific purposes. This paper describes a model applicable for aiding sustained groundwater yield planning and achieving future groundwater quality goals in a system where many cells must contain unsteady pumping as a decision variable or head as a bounded state variable. Included are many constraints describing (1) flow processes that are piecewise linear and (2) transport of dispersed (such as nonpoint source) groundwater contamination. Cited below are relatively recent pertinent studies on optimizing management of groundwater flow (especially in nonlinear systems) or contaminant transport. Comprehensive reviews of earlier models that combine simulation and optimization capability (hereinafter referred to as s/o models) are given by Gorelick [ 1983] and Willis and Yeh [1987]. Within s/o models, hydraulic head response to pumping and stimuli has generally been represented using either embedding or response matrix (RM) methods. In the embedding approach, numerical approximations of the flow equation are included directly as constraints. The RM approach involves more stages. First, a simulation model is used to compute system response to unit pumping rates (linear system responses to these rates have been termed influence coefficients, discrete kernels, algebraic technological functions, and other variants). Second, the s/o model is used to compute optimal pumping strategies. The s/o model uses influence coefficients and superposition to describe system response at specified locations due to pumping. The array of Copyright 1994 by the American Geophysical Union. Paper number 93WR03349. 0043-1397/94/93 WR-03349505.00 influence coefficients used in the superposition equations is termed a response matrix. Embedding models have also been used successfully for transient problems [ Yazicigil and Rasheeduddin, 1987; Willis et al., 1989]. However, embedding models can be unnecessarily large for some situations because they must contain one flow equation per cell per stress period. The s/o models have been most commonly applied to optimize flow within linear (confined) aquifers or aquifers that can be considered linear (having sufficient saturated thickness that changes therein do not significantly affect computed heads). When applied to nonlinear systems, most s/o models have assumed that at least some nonlinear aspects can be treated linearly [e.g.

By extending the concept of response matrix to consider "active" and "passive" effects, an efficient response matrix method is developed for coupling a groundwater simulator and a regional agricultural management model The method eliminates the need to store all of the recovery information from preceding time periods. Active effects are those which occur during the actual application of a pumping or recharge stress while passive effects represent the recovery of water levels from an initial departure from steady-state conditions at the beginning of a time step. Derivation of the required matrices and a numerical example are presented for the Salinas Valley groundwater basin in California.

This work aims to present an industrial perspective on Catalytic Wet Peroxide Oxidation (CWPO) technology. Herein, process simulation and experimental design have been coupled to study the optimal process conditions to ensure high-performance oxidation, minimum H2O2 consumption and maximum energetic efficiency in an industrial scale CWPO unit. The CWPO of phenol in the presence of carbon black catalysts was studied as a model process in the Aspen Plus® v11 simulator. The kinetic model implemented, based on 30 kinetic equations with 11 organic compounds and H2O2 involvement, was valid to describe the complex reaction network and to reproduce the experimental results. The computer experiments were designed on a six-factor Doehlert Matrix in order to describe the influence of the operating conditions (i.e., the different process temperatures, inlet chemical oxygen demands, doses of H2O2 and space time) on each selected output response (conversion, efficiency of H2O2 consumption and ene...

The embedding optimization modeling approach is adapted to aid sustainable groundwater quantity and quality management of complex nonlinear multilayer aquifers. Implicit block-centered finite difference approximations of the quasi three-dimensional unsteady flow equation and Galerkin finite element approximations of the two-dimensional advection-dispersion transport equation are embedded directly as constraints in the model. Also used are nonlinear constraints describing river-aquifer interflow, evapotranspiration, and vertical flow reduction due to unconfinement. These circumvent use of large numbers of integer variables. The use of both linear and nonlinear formulations in a cyclical manner reduces execution time and improves confidence in solution optimality. The methodology is demonstrated for Salt Lake valley where groundwater quantity and quality management are needed, the proportion of pumping cells and cells needing head constraint is large, and many flows are described by discrete nonlinear or piecewise linear functions.

It has always been important to study the development and improvement of the design of turbomachines, owing to the numerous uses of turbomachines and their high energy consumption. Accordingly, optimizing turbomachine performance is crucial for sustainable development. The design of impellers significantly affects the performance of centrifugal compressors. Numerous models and design methods proposed for this subject area, however, old and based on the 1D scheme. The present article developed a hybrid optimization model based on genetic algorithms (GA) and a 3D simulation of compressors to examine the certain parameters such as blade angle at leading and trailing edges and the starting point of splitter blades. New impeller design is proposed to optimize the base compressor. The contribution of this paper includes the automatic creation of generations for achieving the optimal design and designing splitter blades using a novel method. The present study concludes with presenting a ne...

In this paper, a methodology for conjunctive use of surface and groundwater resources with emphasis on water quality is developed using Genetic Algorithms (GAs) and the Artificial Neural Networks (ANNs). Water supply with acceptable quality, reduction of pumping costs, and controlling the groundwater table fluctuations are considered in the objective function of the model. In the proposed methodology, the results of a groundwater simulation model are used to train the ANNs based simulation model. This model is then linked to the GA based optimization model to develop the monthly conjunctive use operating policies. The proposed model is applied to the surface and groundwater allocation in the irrigation networks in the southern part of Tehran, the capital city of Iran. Tehran metropolitan area has annual domestic water consumption close to one billion cubic meters. The sewer system is mainly consisted of the traditional absorption wells. Some part of this sewage is drained into local rivers and drainage channels and partially contaminates the surface runoff and local flows. These polluted surface waters are used in conjunction with groundwater for irrigation purposes in the Southern part of the Tehran. The results of the proposed model show the significance of an integrated and systems approach to surface and groundwater resources allocation in the study area. For example, the cumulative groundwater table variations in each zone, which has experienced a total fluctuation of more than 20 ± meters in the last 20 years, is limited to 5 ± meters over the planning horizon

In this paper, a methodology for conjunctive use of surface and groundwater resources is developed using the combination of the Genetic Algorithms (GAs) and the Artificial Neural Networks (ANN). Water supply to agricultural demands, reduction of pumping costs and control of groundwater table fluctuations are considered in the objective function of the model. In the proposed model, the results of MODFLOW groundwater simulation model are used to train an ANN. The ANN as groundwater response functions is then linked to the GA based optimization model to develop the monthly conjunctive use operating policies. The model is applied to the surface and groundwater allocation for irrigation purposes in the southern part of Tehran. A new ANN is also trained and checked for developing the real-time conjunctive use operating rules. The results show the significance of an integrated approach to surface and groundwater allocation in the study area. A simulation of the optimal policies shows that the cumulative groundwater table variation can be reduced to less than 4 meters from the current devastating condition. The results also show that the proposed model can effectively reduce the run time of the conjunctive use models through the composition of a GA-based optimization and a ANN-based simulation model.

The number of missed appointments in healthcare institutions in Nigeria caused problems, hence the need for integrated healthcare system to intervene and provide seamless care for patients. Appointment scheduling system lies at the intersection of providing efficiency and timely access to health services. This research presents an online National Health Insurance Scheme (NHIS) Outpatient Medical Appointment Booking System where NHIS patients can access and view any available personnel or doctor schedule in order to book an appointment with the corresponding time as specified by the available doctor. The system was developed using PhP, macromedia dreamweaver, apache and MYSQL. This is to ensure that the application is robust, cheap and is able to run on different platforms. The system provides the platform to facilitate the booking and management of patients' appointment bookings. Patients can also view their appointment reports. It also provides the healthcare workers an easy access to manage patients' appointments and to generate relevant reports.

It has always been important to study the development and improvement of the design of turbomachines, owing to the numerous uses of turbomachines and their high energy consumption. Accordingly, optimizing turbomachine performance is crucial for sustainable development. The design of impellers significantly affects the performance of centrifugal compressors. Numerous models and design methods proposed for this subject area, however, old and based on the 1D scheme. The present article developed a hybrid optimization model based on genetic algorithms (GA) and a 3D simulation of compressors to examine the certain parameters such as blade angle at leading and trailing edges and the starting point of splitter blades. New impeller design is proposed to optimize the base compressor. The contribution of this paper includes the automatic creation of generations for achieving the optimal design and designing splitter blades using a novel method. The present study concludes with presenting a new, more efficient, and stable design.

The increasing customization of products, which leads to greater variances and smaller lot sizes, requires highly flexible manufacturing systems. These systems are subject to dynamic influences and demand increasing effort for the generation of feasible production schedules and process control. This paper presents an approach for dealing with these challenges. First, production scheduling is executed by coupling an optimization heuristic with a simulation model. Second, real-time system state data, to be provided by forthcoming cyber-physical systems, is fed back, so that the simulation model is continuously updated and the optimization heuristic can either adjust an existing schedule or generate a new one. The potential of the approach was tested by means of a use case embracing a semiconductor manufacturing facility, in which the simulation results were employed to support the selection of better dispatching rules, improving flexible manufacturing systems performance regarding the average production cycle time.

With an ageing population and more efficient treatments, demand for cancer care is increasing. Therefore, hospitals need to find ways to improve their operational efficiency for cancer care. In this article, we review the contributions in the operations management and operations research (OM/OR) literature that address the planning of outpatient chemotherapy, one of the main treatments for cancer. The distinctive characteristics of outpatient chemotherapy are highlighted. In particular, the interdependence between the administration of chemotherapy drugs in the outpatient clinic and drug preparation in the pharmacy is pointed out. This makes outpatient chemotherapy planning a multiple department challenge where coordination is essential to the global performance of the system. The modeling challenges induced by this interdependence and by the clinical dimension of chemotherapy are presented. Finally, a case study is performed to confront the literature with the reality of a hospital. Important gaps in the literature are outlined, such as the lack of studies taking an integrated, systemic perspective on this multi-department issue.

The extension and application of a queuing network model to the management of core logistic processes at the Gioia Tauro marine container terminal is presented. Real features incorporated in the model require simulation to solve it. A manager-friendly simulator is designed for the real case study, under the constraint of guaranteeing a finer representation of: the congestion phenomenon at the port channel; the port admission policy for newly arrived vessels in the roadstead; the management of berthing slots; the assignment of cranes for discharge/loading operations. The application software is presented through a detailed discussion of its features, as these appear on panel for system definition and analysis. The simulator computes point and interval estimates for system performance measures. Statistical computations are based upon the issue of batching elementary observations either within the same run or across multiple runs. Simulation experiments are presented and discussed with...

In India in recent decades, groundwater has emerged as a principal source for meeting drinking and irrigation needs. As a result, groundwater depletion and over-extraction are acknowledged as major concerns. Different policy interventions are being explored to augment the management of aquifers. Aquifer storage and recovery (ASR) is one such intervention that is becoming popular among government agencies, developmental actors, and even farmers for recharging and recovering water from aquifers. However, the selection of a suitable location and appropriate aquifer for recharge is challenging. The main objective of this study was to classify site selection criteria for ASR installations in different types of aquifers in North India. In this study, both scientific indicators (i.e., rainfall, elevation, soil and aquifer characteristics, surface and groundwater quality) and social characteristics (tacit knowledge, land ownership, willingness to participate) were evaluated to create an integrated ASR site selection criterion. The results indicated that ASR sites could not be appropriately identified solely based on available metrological, geospatial, and geohydrological data. Socioeconomic parameters should be an integral part of the decision-making process for the site selection for ASR. Based on these scientific indicators and social characteristics, a total of seven potential ASR sites (three in the village of Nekpur and four in the village of Meyar) were selected at Rajgir, Nalanda, Bihar, India. Although this integrated site-assessment framework was designed based on 12 indicators in the context of the marginal alluvial plains for the mid-Ganga regions in this study, the general principles adopted in this study can be applied to other regions.

A computationally inexpensive linked ANN-optimization model for planning of groundwater development for agricultural usage is presented and illustrated on a canal command area in India. The planning ensures optimization of zonal crop areas subject to the constraints on maximum groundwater table depth and stream-aquifer interflow under dynamic equilibrium. The data required for developing the ANN models of the envisaged state variables comprise an array of zonal crop areas and the corresponding state variables. These data are generated invoking a pre-calibrated simulation model of groundwater flow.

Water resources are one of the essential natural resources of human life and are one of the most important factors limiting the natural environment, the survival of human societies, and development. On the other hand, phenomena such as climate fluctuations, climate change, population growth, mismanagement, etc. have led to a sharp increase in water resource constraints. In this regard, a proper estimation of this resource is required in the context of sustainable development planning and management strategies. The new approaches in this area are to determine the water resources carrying capacity (WRCC). WRCC is a major component of resource and environmental studies and it is a management concept aimed at supporting sustainable socioeconomic development on a regional scale and catchment areas. Failure to pay attention to concepts such as the carrying capacity in the country's planning has led to the ineffectiveness of most programs. For this purpose, in the present study, it has been tried to use the simulation-optimization approach to determine the  water resources carrying capacity in a pilot basin (Tashk-Bakhtegan Basin), considering the economic, environmental and Water resources in the historical periods (1985-2014) and terms of climate change (2045-2015) should be considered. In this regard, the Water and Soil Assessment Tool (SWAT) and the Genetic Algorithm are used. For this purpose, the outputs of three general circulation atmosphere models under RCP 2.6, 4.5, 8.5 scenarios have been used to assess climate change in this study. The results of the study indicate overloading of water resources due to increased crop area in all studied periods. Also, the water resources carrying capacity due to climate fluctuations and climate change in the examined period (1985 - 2045) has been declining, and from 2.6 billion cubic meters in the period (1985-2006) to 1.9 billion cubic meters. The most pessimistic climatic conditions are reduced.

Modern companies have to face challenging configuration issues in their manufacturing chains. One of these challenges is related to the integrated allocation and scheduling of resources such as machines, workers, energy, etc. These integrated optimization problems are difficult to solve, but they can be even more challenging when real-life uncertainty is considered. In this paper, we study an integrated allocation and scheduling optimization problem with stochastic processing times. A simheuristic algorithm is proposed in order to effectively solve this integrated and stochastic problem. Our approach relies on the hybridization of simulation with a metaheuristic to deal with the stochastic version of the allocation-scheduling problem. A series of numerical experiments contribute to illustrate the efficiency of our methodology as well as their potential applications in real-life enterprise settings.

In this article a new algorithm is developed for optimizing computationally expensive simulation models. The optimization algorithm is developed for continues unconstrained single output simulation models. The algorithm is developed using two simulation optimization routines. We employed the nested partitioning (NP) routine for concentrating the search efforts in the regions which are most likely contained the global optimum, and we used the experimental design concept for selecting most promising points. Then we integrated the Particle Swarm Optimization (PSO) routine as the searching mechanism of the developed algorithm to single out the best point (optimal or a near optimal solution). Through these integrations, an algorithm was developed which is capable of optimizing digital simulation models. The efficiency of the developed algorithm was then evaluated through a computational experiment. Ten test problems were selected from the literature and the efficiency of the PSPO algorit...

Electronic systems are usually required to maintain the value of their parameters within set limits over a wide range of conditions, for large variations of internal or external factors. Given the large number of factors that need be considered it is often un-practical to check all and each combination of factors. New approaches, such as the parameter design, are necessary for designing robust systems, with defined performance for all operational conditions, while keeping the development time and production cost to acceptably low levels. This paper describes two methods for parameter design: the classical, analytical approach, based on underlying assumptions and a new simulation based methodology, focused on real-life cases. The proposed method helps the designer to bring a system response to the target and reduce its sensitivity to varying operating conditions. It is demonstrated on a real-life case: optimized sizing of the external circuitry of a low dropout voltage regulator, wit...

Advances in facility design and technology are leading to novel uses of healthcare delivery space including flexible and shared clinical space increasing collaboration and communication in multidisciplinary care settings. With new outpatient care delivery facilities and plans emerging, the need to evaluate how flexible and shared resources are assigned arises. We present a discrete-event simulation model based on the daily operations of an outpatient clinic where multiple specialties share resources including support staff, exam rooms, and ancillary providers. Being a new clinical space, the primary objective is to design resource assignment and staffing policies which maximize the use of the new facility. While resource utilization is the primary objective, the simulation model results and analysis incorporate other competing performance criteria including patient waiting, provider idleness, and clinic length of day. Results are presented based on a multidisciplinary clinic at the ...