The linked simulation-optimization model can be used for solving a complex groundwater pollution source identification problem. Advanced simulators have been developed and successfully linked with numerous optimizatio...The linked simulation-optimization model can be used for solving a complex groundwater pollution source identification problem. Advanced simulators have been developed and successfully linked with numerous optimization algorithms for identification of groundwater pollution sources. However, the identification of pollution sources in a groundwater aquifer using linked simulation-optimization model has proven to be computationally expensive. To overcome this computational burden, an approximate simulator, the artificial neural network (ANN) model can be used as a surrogate model to replace the complex time-consuming numerical simulation model. However, for large-scale aquifer system, the performance of the ANN-based surrogate model is not satisfactory when a single ANN model is used to predict the concentration at different observation locations. In such a situation, the model efficiency can be enhanced by developing separate ANN model for each of the observation locations. The number of ANN models is equal to the number of observation wells in the aquifer. As a result, the complexity of the ANN-based simulation-optimization model will be related to the number of observation wells. Thus, this study used a modified formulation to find out the optimal numbers of observation wells which will eventually reduce the computational time of the model. The performance of the ANN-based simulation-optimization model is evaluated by identifying the groundwater pollutant sources of a hypothetical study area. The limited evaluation shows that the model has the potential for field application.展开更多
This paper proposes a new storage allocation rule based on target storage curves. Joint operating rules are also proposed to solve the operation problems of a multi-reservoir system with joint demands and water transf...This paper proposes a new storage allocation rule based on target storage curves. Joint operating rules are also proposed to solve the operation problems of a multi-reservoir system with joint demands and water transfer-supply projects. The joint operating rules include a water diversion rule to determine the amount of diverted water in a period, a hedging rule based on an aggregated reservoir to determine the total release from the system, and a storage allocation rule to specify the release from each reservoir. A simulation-optimization model was established to optimize the key points of the water diversion curves, the hedging rule curves, and the target storage curves using the improved particle swarm optimization （IPSO） algorithm. The multi-reservoir water supply system located in Liaoning Province, China, including a water transfer-supply project, was employed as a case study to verify the effectiveness of the proposed join operating rules and target storage curves. The results indicate that the proposed operating rules are suitable for the complex system. The storage allocation rule based on target storage curves shows an improved performance with regard to system storage distribution.展开更多
Effective management of water resources,especially groundwater,is crucial and requires a precise understanding of aquifer characteristics,imposed stresses,and the groundwater balance.Simulation-optimization models pla...Effective management of water resources,especially groundwater,is crucial and requires a precise understanding of aquifer characteristics,imposed stresses,and the groundwater balance.Simulation-optimization models plays a vital role in guiding planners toword sustainable long-term aquifer exploita-tion.This study simulated monthly water table variations in the Kashan Plain over a ten-year period from 2008 to 2019 across 125 stress periods using the GMS model.The model was calibrated for both steady-state and transient conditions for the 2008–2016 period and validated for the 2016–2019 period.Results indicated a 4.4 m decline in groundwater levels over the 10-year study period.Given the plain's location in a arid climatic zone with limited effective precipitation for aquifer recharge,the study focused on ground-water extraction management.A modified two-point hedging policy was employed as a solution to mitigate critical groundwater depletion,reducing the annual drawdown rate from 0.44 m to 0.31 m and conserving 255 million cubic meters(mcm)of water annually.Although this approach slightly decreased reliability(i.e.the number of months meeting full water demands),it effectively minimized the risk of severe droughts and irreparable damages.This policy offers managers a dynamical and intelligent tool for regulating groundwater extraction,balancing aquifer sustainability with agricultural and urban water requirements.展开更多
Rockfalls are one of the hazards that may be associated with open pit mining. The majority of rockfalls occur due to the existing conditions of slopes, such as back break, fractures and joints. Constructing a berm on ...Rockfalls are one of the hazards that may be associated with open pit mining. The majority of rockfalls occur due to the existing conditions of slopes, such as back break, fractures and joints. Constructing a berm on the catch bench is a popular method for the mitigation of rockfall hazards in open pit mining.The width of the catch bench and the height of the berm play a major role in the open pit bench design.However, there is no systematic method currently available to optimize the size of these parameters. This study proposes a novel methodology which calculates the optimum catch bench width by integrating the rockfall simulation model and genetic algorithm into a Simulation-Optimization Model. The proposed methodology is useful when used to determine the minimum catch bench width, or the maximum overall slope angle, insuring that a sufficient factor of safety of the slope is included while maximizing the overall profitability of the open pit mine.展开更多
With every passing day,the demand for data traffic is increasing,and this urges the research community not only to look for an alternating spectrum for communication but also urges radio frequency planners to use the ...With every passing day,the demand for data traffic is increasing,and this urges the research community not only to look for an alternating spectrum for communication but also urges radio frequency planners to use the existing spectrum efficiently.Cell sizes are shrinking with every upcoming communication generation,which makes base station placement planning even more complex and cumbersome.In order to make the next-generation cost-effective,it is important to design a network in such a way that it utilizes the minimum number of base stations while ensuring seamless coverage and quality of service.This paper aims at the development of a new simulation-based optimization approach using a hybrid metaheuristic and metamodel applied in a novel mathematical formulation of the multi-transmitter placement planning(MTPP)problem.We first develop a new mathematical programming model for MTPP that is flexible to design the locations for any number of transmitters.To solve this constrained optimization problem,we propose a hybrid approach using the radial basis function(RBF)metamodel to assist the particle swarm optimizer(PSO)by mitigating the associated computational burden of the optimization procedure.We evaluate the effectiveness and applicability of the proposed algorithm by simulating the MTPP model with two,three,four and five transmitters and estimating the Pareto front for optimal locations of transmitters.The quantitative results show that almost maximum signal coverage can be obtained with four transmitters;thus,it is not a wise idea to use higher number of transmitters in the model.Furthermore,the limitations and future works are discussed.展开更多
This study proposes a groundwater management model in which the solution is performed through a combined simulation-optimization model. In the proposed model, a modular three-dimensional finite difference groundwater ...This study proposes a groundwater management model in which the solution is performed through a combined simulation-optimization model. In the proposed model, a modular three-dimensional finite difference groundwater flow model, MODFLOW is used as simulation model. This model is then integrated with an optimization model, in which a modified Pareto dominance based Real-Coded Genetic Algorithm (mPRCGA) is adopted. The performance of the proposed mPRCGA based management model is tested on a hypothetical numerical example. The results indicate that the proposed mPRCGA based management model is an effective way to obtain good optimum management strategy and may be used to solve other type of groundwater simulation-optimization problems.展开更多
The slope instability and uneven settlement caused by the foundation pit dewatering pose a great threat to the project and surrounding environment.Thus,it is necessary to carry out optimization design of the foundatio...The slope instability and uneven settlement caused by the foundation pit dewatering pose a great threat to the project and surrounding environment.Thus,it is necessary to carry out optimization design of the foundation pit dewatering project.To solve this problem,this paper introduces the simulation-optimization method and establishes the groundwater model based on MODFLOW-2005.The local grid refinement(LGR)technique is employed to achieve the refinement of dewatering area.Under the premise of construction safety,the minimum cost of the project is set as the objective function to solve the optimization problem of foundation pit engineering with GWM-2005.The results show that the optimization with GWM-2005 will be more accurate combined with the LGR model,but the improvement of the optimization is not obvious.It is necessary to choose a suitable local refinement model considering the engineering requirement.展开更多
Background: Bioenergy is re-shaping opportunities and imperatives of forest management. This study demonstrates,through a case study in Scots pine(Pinus sylvestris L.), how forest bioenergy policies affect stand manag...Background: Bioenergy is re-shaping opportunities and imperatives of forest management. This study demonstrates,through a case study in Scots pine(Pinus sylvestris L.), how forest bioenergy policies affect stand management strategies.Methods: Optimization studies were examined for 15 Scots pine stands of different initial stand densities, site types, and temperature sum regions in Finland. Stand development was model ed using the Pipe Qual stand simulator coupled with the simulation-optimization tool Opti For Bioenergy to assess three forest bioenergy policies on energy wood harvest from early thinnings.Results: The optimal solutions maximizing bare land value indicate that conventional forest management regimes remain optimal for sparse stands. Energy harvests occurred only when profitable, led to lower financial returns. A forest bioenergy policy which included compulsory energy wood harvesting was optimal for denser stands. At a higher interest rate(4 %), increasing energy wood price postponed energy wood harvesting. In addition, our results show that early thinning somewhat reduced wood quality for stands in fertile sites. For less fertile sites, the changes were insignificant.Conclusions: A constraint of profitable energy wood harvest is not rational. It is optimal to carry out the first thinning with a flexible forest bioenergy policy depending on stand density.展开更多
This paper reviews several recently-developed techniques for the minimum-cost optimal design of water-retaining structures (WRSs), which integrate the effects of seepage. These include the incorporation of uncertainty...This paper reviews several recently-developed techniques for the minimum-cost optimal design of water-retaining structures (WRSs), which integrate the effects of seepage. These include the incorporation of uncertainty in heterogeneous soil parameter estimates and quantification of reliability. This review is limited to methods based on coupled simulation-optimization (S-O) models. In this context, the design of WRSs is mainly affected by hydraulic design variables such as seepage quantities, which are difficult to determine from closed-form solutions or approximation theories. An S-O model is built by integrating numerical seepage modeling responses to an optimization algorithm based on efficient surrogate models. The surrogate models (meta-models) are trained on simulated data obtained from finite element numerical code solutions. The proposed methodology is applied using several machine learning techniques and optimization solvers to optimize the design of WRS by incorporating different design variables and boundary conditions. Additionally, the effects of several scenarios of flow domain hydraulic conductivity are integrated into the S-O model. Also, reliability based optimum design concepts are incorporated in the S-O model to quantify uncertainty in seepage quantities due to uncertainty in hydraulic conductivity estimates. We can conclude that the S-O model can efficiently optimize WRS designs. The ANN, SVM, and GPR machine learning technique-based surrogate models are efficiently and expeditiously incorporated into the S-O models to imitate the numerical responses of simulations of various problems.展开更多
Precise identification of the pollutant source characteristics is the first step for designing an effective groundwater contamination remediation strategy. In this study a linked simulation-optimization based methodol...Precise identification of the pollutant source characteristics is the first step for designing an effective groundwater contamination remediation strategy. In this study a linked simulation-optimization based methodology is utilized for identification of unknown groundwater pollution sources in a real life contaminated aquifer in New South Wales, Australia where the source locations and source flux release history are the explicit unknown variables. The methodology is applied utilizing an in house software package GWSID developed at James Cook University for optimal determination of the unknown source characteristics. The methodology incorporates linked simulation optimization approach and utilizes simulated Algorithm as an evolutionary optimization algorithm. The performance evaluation results show practical utility of the methodology and of the associated developed computers software in identifying the unknown source characteristics.展开更多
The confined aquifer dewatering for long-deep excavations usually encounters challenges due to complicated geotechnical conditions,large excavation sizes,and high hydraulic pressures.To propose the most efficient sche...The confined aquifer dewatering for long-deep excavations usually encounters challenges due to complicated geotechnical conditions,large excavation sizes,and high hydraulic pressures.To propose the most efficient scheme of confined aquifer dewatering for long-deep excavations,dewatering optimizations were performed using the simulation–optimization method.An open cut tunnel of the Jiangyin-Jingjiang Yangtze River Tunnel Project was taken as an example.The methods of finite element and linear programming(LP)were combined to optimize the dewatering process.A three-dimensional finite element model was developed.After simulating the pumping tests,hydraulic conductivity was inverted.Then,necessary parameters in the LP method were determined by simulating dewatering with each pumping well,and various LP models were developed based on some important influence factors such as dewatering sequence,considered pumping wells,and pumping rate limitation.Finally,the optimal pumping rates were solved and applied to the numerical model,with induced drawdown and ground settlement computed for comparison.The results indicate that the optimization can significantly reduce the required wells in the original design.Dewatering in the deepest zone exhibits the highest efficiency for long-deep excavations with gradually varying depths.For the dewatering sequence from the shallowest to the deepest zone,more pumping wells are required but less energy is consumed.Higher quantity and more advantageous locations of pumping wells in the LP model usually result in lower total pumping rate,drawdown,and ground settlement.If more pumping wells are considered in the deepest zone,pumping rate limitation of single well will only slightly increase the total pumping rate,number of required pumping wells,drawdown,and ground settlement.展开更多
The purpose of emergency medical systems(EMS)is to save lives and reduce injuries with a quick response in emergencies.The performance of these systems is highly dependent on the locations of ambulances and the policy...The purpose of emergency medical systems(EMS)is to save lives and reduce injuries with a quick response in emergencies.The performance of these systems is highly dependent on the locations of ambulances and the policy for dispatching them to the customers(i.e.,patients).In this study,two new mathematical models are presented to combine the decisions about the location and dispatching policy by integrating the location and hypercube queuing models.In the presented models,the flow-balance equations of the hypercube queuing model are considered as the constraints of the location model.In the first model,the status of each server is idle or busy at any moment,as in the classic hypercube queuing model.In the second model,the travel time is considered independent of the on-scene time,and the status of each server is idle,busy,and traveling,or busy and serving a customer on the incident site.To verify the models,some small-sized examples are first solved exactly.Then,an optimization framework based on the genetic algorithm is presented due to the complexity of the models for solving larger-sized examples.Two approaches(i.e.,the exact and simulation-optimization)are used to extend the framework.The results demonstrate that the proposed optimization framework can obtain proper solutions compared to those of the exact method.Finally,several performance measures are considered that can only be calculated using the second model.展开更多
文摘The linked simulation-optimization model can be used for solving a complex groundwater pollution source identification problem. Advanced simulators have been developed and successfully linked with numerous optimization algorithms for identification of groundwater pollution sources. However, the identification of pollution sources in a groundwater aquifer using linked simulation-optimization model has proven to be computationally expensive. To overcome this computational burden, an approximate simulator, the artificial neural network (ANN) model can be used as a surrogate model to replace the complex time-consuming numerical simulation model. However, for large-scale aquifer system, the performance of the ANN-based surrogate model is not satisfactory when a single ANN model is used to predict the concentration at different observation locations. In such a situation, the model efficiency can be enhanced by developing separate ANN model for each of the observation locations. The number of ANN models is equal to the number of observation wells in the aquifer. As a result, the complexity of the ANN-based simulation-optimization model will be related to the number of observation wells. Thus, this study used a modified formulation to find out the optimal numbers of observation wells which will eventually reduce the computational time of the model. The performance of the ANN-based simulation-optimization model is evaluated by identifying the groundwater pollutant sources of a hypothetical study area. The limited evaluation shows that the model has the potential for field application.
基金supported by the National Natural Science Foundation of China(Grants No.51339004 and 71171151)
文摘This paper proposes a new storage allocation rule based on target storage curves. Joint operating rules are also proposed to solve the operation problems of a multi-reservoir system with joint demands and water transfer-supply projects. The joint operating rules include a water diversion rule to determine the amount of diverted water in a period, a hedging rule based on an aggregated reservoir to determine the total release from the system, and a storage allocation rule to specify the release from each reservoir. A simulation-optimization model was established to optimize the key points of the water diversion curves, the hedging rule curves, and the target storage curves using the improved particle swarm optimization （IPSO） algorithm. The multi-reservoir water supply system located in Liaoning Province, China, including a water transfer-supply project, was employed as a case study to verify the effectiveness of the proposed join operating rules and target storage curves. The results indicate that the proposed operating rules are suitable for the complex system. The storage allocation rule based on target storage curves shows an improved performance with regard to system storage distribution.
文摘Effective management of water resources,especially groundwater,is crucial and requires a precise understanding of aquifer characteristics,imposed stresses,and the groundwater balance.Simulation-optimization models plays a vital role in guiding planners toword sustainable long-term aquifer exploita-tion.This study simulated monthly water table variations in the Kashan Plain over a ten-year period from 2008 to 2019 across 125 stress periods using the GMS model.The model was calibrated for both steady-state and transient conditions for the 2008–2016 period and validated for the 2016–2019 period.Results indicated a 4.4 m decline in groundwater levels over the 10-year study period.Given the plain's location in a arid climatic zone with limited effective precipitation for aquifer recharge,the study focused on ground-water extraction management.A modified two-point hedging policy was employed as a solution to mitigate critical groundwater depletion,reducing the annual drawdown rate from 0.44 m to 0.31 m and conserving 255 million cubic meters(mcm)of water annually.Although this approach slightly decreased reliability(i.e.the number of months meeting full water demands),it effectively minimized the risk of severe droughts and irreparable damages.This policy offers managers a dynamical and intelligent tool for regulating groundwater extraction,balancing aquifer sustainability with agricultural and urban water requirements.
文摘Rockfalls are one of the hazards that may be associated with open pit mining. The majority of rockfalls occur due to the existing conditions of slopes, such as back break, fractures and joints. Constructing a berm on the catch bench is a popular method for the mitigation of rockfall hazards in open pit mining.The width of the catch bench and the height of the berm play a major role in the open pit bench design.However, there is no systematic method currently available to optimize the size of these parameters. This study proposes a novel methodology which calculates the optimum catch bench width by integrating the rockfall simulation model and genetic algorithm into a Simulation-Optimization Model. The proposed methodology is useful when used to determine the minimum catch bench width, or the maximum overall slope angle, insuring that a sufficient factor of safety of the slope is included while maximizing the overall profitability of the open pit mine.
基金funded by TSRI Fund(CU_FRB640001_01_21_6).Amir Parnianifard would like to acknowledge the financial support by Second Century Fund(C2F),Chulalongkorn University,BangkokSupporting Project number(TURSP-2020/228),Taif University,Taif,Saudi Arabia for the financial support.
文摘With every passing day,the demand for data traffic is increasing,and this urges the research community not only to look for an alternating spectrum for communication but also urges radio frequency planners to use the existing spectrum efficiently.Cell sizes are shrinking with every upcoming communication generation,which makes base station placement planning even more complex and cumbersome.In order to make the next-generation cost-effective,it is important to design a network in such a way that it utilizes the minimum number of base stations while ensuring seamless coverage and quality of service.This paper aims at the development of a new simulation-based optimization approach using a hybrid metaheuristic and metamodel applied in a novel mathematical formulation of the multi-transmitter placement planning(MTPP)problem.We first develop a new mathematical programming model for MTPP that is flexible to design the locations for any number of transmitters.To solve this constrained optimization problem,we propose a hybrid approach using the radial basis function(RBF)metamodel to assist the particle swarm optimizer(PSO)by mitigating the associated computational burden of the optimization procedure.We evaluate the effectiveness and applicability of the proposed algorithm by simulating the MTPP model with two,three,four and five transmitters and estimating the Pareto front for optimal locations of transmitters.The quantitative results show that almost maximum signal coverage can be obtained with four transmitters;thus,it is not a wise idea to use higher number of transmitters in the model.Furthermore,the limitations and future works are discussed.
文摘This study proposes a groundwater management model in which the solution is performed through a combined simulation-optimization model. In the proposed model, a modular three-dimensional finite difference groundwater flow model, MODFLOW is used as simulation model. This model is then integrated with an optimization model, in which a modified Pareto dominance based Real-Coded Genetic Algorithm (mPRCGA) is adopted. The performance of the proposed mPRCGA based management model is tested on a hypothetical numerical example. The results indicate that the proposed mPRCGA based management model is an effective way to obtain good optimum management strategy and may be used to solve other type of groundwater simulation-optimization problems.
基金funded by Nanning Rail Transit Co., Ltd.the joint Foundation of Key Laboratory of Institute of Hydrogeology and Environmental Geology CAGS grant number (KF201611)
文摘The slope instability and uneven settlement caused by the foundation pit dewatering pose a great threat to the project and surrounding environment.Thus,it is necessary to carry out optimization design of the foundation pit dewatering project.To solve this problem,this paper introduces the simulation-optimization method and establishes the groundwater model based on MODFLOW-2005.The local grid refinement(LGR)technique is employed to achieve the refinement of dewatering area.Under the premise of construction safety,the minimum cost of the project is set as the objective function to solve the optimization problem of foundation pit engineering with GWM-2005.The results show that the optimization with GWM-2005 will be more accurate combined with the LGR model,but the improvement of the optimization is not obvious.It is necessary to choose a suitable local refinement model considering the engineering requirement.
基金partly supported by GSForest in Finland and National Natural Science Foundation of China(NSFC 31170586)
文摘Background: Bioenergy is re-shaping opportunities and imperatives of forest management. This study demonstrates,through a case study in Scots pine(Pinus sylvestris L.), how forest bioenergy policies affect stand management strategies.Methods: Optimization studies were examined for 15 Scots pine stands of different initial stand densities, site types, and temperature sum regions in Finland. Stand development was model ed using the Pipe Qual stand simulator coupled with the simulation-optimization tool Opti For Bioenergy to assess three forest bioenergy policies on energy wood harvest from early thinnings.Results: The optimal solutions maximizing bare land value indicate that conventional forest management regimes remain optimal for sparse stands. Energy harvests occurred only when profitable, led to lower financial returns. A forest bioenergy policy which included compulsory energy wood harvesting was optimal for denser stands. At a higher interest rate(4 %), increasing energy wood price postponed energy wood harvesting. In addition, our results show that early thinning somewhat reduced wood quality for stands in fertile sites. For less fertile sites, the changes were insignificant.Conclusions: A constraint of profitable energy wood harvest is not rational. It is optimal to carry out the first thinning with a flexible forest bioenergy policy depending on stand density.
文摘This paper reviews several recently-developed techniques for the minimum-cost optimal design of water-retaining structures (WRSs), which integrate the effects of seepage. These include the incorporation of uncertainty in heterogeneous soil parameter estimates and quantification of reliability. This review is limited to methods based on coupled simulation-optimization (S-O) models. In this context, the design of WRSs is mainly affected by hydraulic design variables such as seepage quantities, which are difficult to determine from closed-form solutions or approximation theories. An S-O model is built by integrating numerical seepage modeling responses to an optimization algorithm based on efficient surrogate models. The surrogate models (meta-models) are trained on simulated data obtained from finite element numerical code solutions. The proposed methodology is applied using several machine learning techniques and optimization solvers to optimize the design of WRS by incorporating different design variables and boundary conditions. Additionally, the effects of several scenarios of flow domain hydraulic conductivity are integrated into the S-O model. Also, reliability based optimum design concepts are incorporated in the S-O model to quantify uncertainty in seepage quantities due to uncertainty in hydraulic conductivity estimates. We can conclude that the S-O model can efficiently optimize WRS designs. The ANN, SVM, and GPR machine learning technique-based surrogate models are efficiently and expeditiously incorporated into the S-O models to imitate the numerical responses of simulations of various problems.
文摘Precise identification of the pollutant source characteristics is the first step for designing an effective groundwater contamination remediation strategy. In this study a linked simulation-optimization based methodology is utilized for identification of unknown groundwater pollution sources in a real life contaminated aquifer in New South Wales, Australia where the source locations and source flux release history are the explicit unknown variables. The methodology is applied utilizing an in house software package GWSID developed at James Cook University for optimal determination of the unknown source characteristics. The methodology incorporates linked simulation optimization approach and utilizes simulated Algorithm as an evolutionary optimization algorithm. The performance evaluation results show practical utility of the methodology and of the associated developed computers software in identifying the unknown source characteristics.
基金supported by the National Natural Science Foundation of China(Grant Nos.41972269 and 52178384)the Project of Jiangsu Provincial Transportation Construction Bureau,China(Grant No.2021QD05).
文摘The confined aquifer dewatering for long-deep excavations usually encounters challenges due to complicated geotechnical conditions,large excavation sizes,and high hydraulic pressures.To propose the most efficient scheme of confined aquifer dewatering for long-deep excavations,dewatering optimizations were performed using the simulation–optimization method.An open cut tunnel of the Jiangyin-Jingjiang Yangtze River Tunnel Project was taken as an example.The methods of finite element and linear programming(LP)were combined to optimize the dewatering process.A three-dimensional finite element model was developed.After simulating the pumping tests,hydraulic conductivity was inverted.Then,necessary parameters in the LP method were determined by simulating dewatering with each pumping well,and various LP models were developed based on some important influence factors such as dewatering sequence,considered pumping wells,and pumping rate limitation.Finally,the optimal pumping rates were solved and applied to the numerical model,with induced drawdown and ground settlement computed for comparison.The results indicate that the optimization can significantly reduce the required wells in the original design.Dewatering in the deepest zone exhibits the highest efficiency for long-deep excavations with gradually varying depths.For the dewatering sequence from the shallowest to the deepest zone,more pumping wells are required but less energy is consumed.Higher quantity and more advantageous locations of pumping wells in the LP model usually result in lower total pumping rate,drawdown,and ground settlement.If more pumping wells are considered in the deepest zone,pumping rate limitation of single well will only slightly increase the total pumping rate,number of required pumping wells,drawdown,and ground settlement.
文摘The purpose of emergency medical systems(EMS)is to save lives and reduce injuries with a quick response in emergencies.The performance of these systems is highly dependent on the locations of ambulances and the policy for dispatching them to the customers(i.e.,patients).In this study,two new mathematical models are presented to combine the decisions about the location and dispatching policy by integrating the location and hypercube queuing models.In the presented models,the flow-balance equations of the hypercube queuing model are considered as the constraints of the location model.In the first model,the status of each server is idle or busy at any moment,as in the classic hypercube queuing model.In the second model,the travel time is considered independent of the on-scene time,and the status of each server is idle,busy,and traveling,or busy and serving a customer on the incident site.To verify the models,some small-sized examples are first solved exactly.Then,an optimization framework based on the genetic algorithm is presented due to the complexity of the models for solving larger-sized examples.Two approaches(i.e.,the exact and simulation-optimization)are used to extend the framework.The results demonstrate that the proposed optimization framework can obtain proper solutions compared to those of the exact method.Finally,several performance measures are considered that can only be calculated using the second model.
