Byproduct gas is an important secondary energy in iron and steel industry, and its optimization is vital to cost reduction. With the development of iron and steel industry to be more eco-friendly, it is necessary to c...Byproduct gas is an important secondary energy in iron and steel industry, and its optimization is vital to cost reduction. With the development of iron and steel industry to be more eco-friendly, it is necessary to construct an integrated optimized system, taking economics, energy consumption and environment into consideration. Therefore, the environmental cost caused by pollutants discharge should be factored in total cost when optimizing byproduct gas distribution. A green mixed integer linear programming （MILP） model for the optimization of byproduct gases was established to reduce total cost, including both operation cost and environmental cost. The operation cost included penalty for gas deviation, costs of fuel and water consumption, holder booster trip penalty, and so forth; while the environmental cost consisted of penalties for both direct and indirect pollutants discharge. Case study showed that the proposed model brought an optimum solution and 2.2% of the total cost could be reduced compared with previous one.展开更多
In this study, we aimed to assess the solution quality for location-allocation problems from facilities generated by the software TransCAD®?, a Geographic Information System for Transportation (GIS-T). Such fa...In this study, we aimed to assess the solution quality for location-allocation problems from facilities generated by the software TransCAD®?, a Geographic Information System for Transportation (GIS-T). Such facilities were obtained after using two routines together: Facility Location and Transportation Problem, when compared with optimal solutions from exact mathematical models, based on Mixed Integer Linear Programming (MILP), developed externally for the GIS. The models were applied to three simulations: the first one proposes opening factories and customer allocation in the state of Sao Paulo, Brazil;the second involves a wholesaler and a study of location and allocation of distribution centres for retail customers;and the third one involves the location of day-care centers and allocation of demand (0 - 3 years old children). The results showed that when considering facility capacity, the MILP optimising model presents results up to 37% better than the GIS and proposes different locations to open new facilities.展开更多
This paper proposes a deterministic two-stage mixed integer linear programming(TSMILP)approach to solve the reserve constrained dynamic economic dispatch(DED)problem considering valve-point effect(VPE).In stage one,th...This paper proposes a deterministic two-stage mixed integer linear programming(TSMILP)approach to solve the reserve constrained dynamic economic dispatch(DED)problem considering valve-point effect(VPE).In stage one,the nonsmooth cost function and the transmission loss are piecewise linearized and consequently the DED problem is formulated as a mixed integer linear programming(MILP)problem,which can be solved by commercial solvers.In stage two,based on the solution obtained in stage one,a range compression technique is proposed to make a further exploitation in the subspace of the whole solution domain.Due to the linear approximation of the transmission loss,the solution obtained in stage two dose not strictly satisfies the power balance constraint.Hence,a forward procedure is employed to eliminate the error.The simulation results on four test systems show that TSMILP makes satisfactory performances,in comparison with the existing methods.展开更多
A novel mixed integer linear programming (NMILP) model for detection of gross errors is presented in this paper. Yamamura et al.(1988) designed a model for detection of gross errors and data reconciliation based on Ak...A novel mixed integer linear programming (NMILP) model for detection of gross errors is presented in this paper. Yamamura et al.(1988) designed a model for detection of gross errors and data reconciliation based on Akaike information cri- terion (AIC). But much computational cost is needed due to its combinational nature. A mixed integer linear programming (MILP) approach was performed to reduce the computational cost and enhance the robustness. But it loses the super performance of maximum likelihood estimation. To reduce the computational cost and have the merit of maximum likelihood estimation, the simultaneous data reconciliation method in an MILP framework is decomposed and replaced by an NMILP subproblem and a quadratic programming (QP) or a least squares estimation (LSE) subproblem. Simulation result of an industrial case shows the high efficiency of the method.展开更多
The rapid evolution of unmanned aerial vehicle(UAV)technology and autonomous capabilities has positioned UAV as promising last-mile delivery means.Vehicle and onboard UAV collaborative delivery is introduced as a nove...The rapid evolution of unmanned aerial vehicle(UAV)technology and autonomous capabilities has positioned UAV as promising last-mile delivery means.Vehicle and onboard UAV collaborative delivery is introduced as a novel delivery mode.Spatiotemporal collaboration,along with energy consumption with payload and wind conditions play important roles in delivery route planning.This paper introduces the traveling salesman problem with time window and onboard UAV(TSPTWOUAV)and emphasizes the consideration of real-world scenarios,focusing on time collaboration and energy consumption with wind and payload.To address this,a mixed integer linear programming(MILP)model is formulated to minimize the energy consumption costs of vehicle and UAV.Furthermore,an adaptive large neighborhood search(ALNS)algorithm is applied to identify high-quality solutions efficiently.The effectiveness of the proposed model and algorithm is validated through numerical tests on real geographic instances and sensitivity analysis of key parameters is conducted.展开更多
In this paper,a mixed integer linear programming(MILP)formulation for robust state estimation(RSE)is proposed.By using the exactly linearized measurement equations instead of the original nonlinear ones,the existingmi...In this paper,a mixed integer linear programming(MILP)formulation for robust state estimation(RSE)is proposed.By using the exactly linearized measurement equations instead of the original nonlinear ones,the existingmixed integer nonlinear programming formulation for RSE is converted to a MILP problem.The proposed approach not only guarantees to find the global optimum,but also does not have convergence problems.Simulation results on a rudimentary 3-bus system and several IEEE standard test systems fully illustrate that the proposed methodology is effective with high efficiency.展开更多
Finding the accurate solution for N-vehicle exploration problem is NP-hard in strong sense.In this paper,authors build a linear mixed integer programming model for N-vehicle exploration problem based on its properties...Finding the accurate solution for N-vehicle exploration problem is NP-hard in strong sense.In this paper,authors build a linear mixed integer programming model for N-vehicle exploration problem based on its properties.The model is then proved equivalent to the original problem.Given the model,one can apply the already existed methods and algorithms for mixed integer linear programming on N-vehicle exploration problem,which helps to enrich methods for solving N-vehicle exploration problem.展开更多
Commercial organisations commonly use operational research tools to solve vehicle routing problems. This practice is less commonplace in charity and voluntary organisations. In this paper, we provide an elementary app...Commercial organisations commonly use operational research tools to solve vehicle routing problems. This practice is less commonplace in charity and voluntary organisations. In this paper, we provide an elementary approach for solving the Vehicle Routing Problem (VRP) that we believe can be easily implemented in these types of organisations. The proposed model leverages mixed integer linear programming to optimize the pickup sequence of all customers, each with distinct time windows and locations, transporting them to a final destination using a fleet of vehicles. To ensure ease of implementation, the model utilises Python, a user-friendly programming language, and integrates with the Google Maps API, which simplifies data input by eliminating the need for manual entry of travel times between locations. Troubleshooting methods are incorporated into the model design to ensure easy debugging of the model’s infeasibilities. Additionally, a computation time analysis is conducted to evaluate the efficiency of the code. A node partitioning approach is also discussed, which aims to reduce computational times, especially when handling larger datasets, ensuring this model is realistic and practical for real-world application. By implementing this optimized routing strategy, logistics companies or organisations can expect significant improvements in their day-to-day operations, with minimal computational cost or need for specialised expertise. This includes reduced travel times, minimized fuel consumption, and thus lower operational costs, while ensuring punctuality and meeting the demands of all passengers.展开更多
Near-surface deposits that extend to considerable depths are often amenable to both open pit mining and/or underground mining.This paper investigates the strategy of mining options for an orebody using a Mixed Integer...Near-surface deposits that extend to considerable depths are often amenable to both open pit mining and/or underground mining.This paper investigates the strategy of mining options for an orebody using a Mixed Integer Linear Programming(MILP)optimization framework.The MILP formulation maximizes the Net Present Value(NPV)of the reserve when extracted with(i)open pit mining,(ii)underground mining,and(iii)concurrent open pit and underground mining.Comparatively,implementing open pit mining generates a higher NPV than underground mining.However considering the investment required for these mining options,underground mining generates a better return on investment than open pit mining.Also,in the concurrent open pit and underground mining scenario,the optimizer prefers extracting blocks using open pit mining.Although the underground mine could access ore sooner,the mining cost differential for open pit mining is more than compensated for by the discounting benefits associated with earlier underground mining.展开更多
Cloud computing involves remote server deployments with public net-work infrastructures that allow clients to access computational resources.Virtual Machines(VMs)are supplied on requests and launched without interacti...Cloud computing involves remote server deployments with public net-work infrastructures that allow clients to access computational resources.Virtual Machines(VMs)are supplied on requests and launched without interactions from service providers.Intruders can target these servers and establish malicious con-nections on VMs for carrying out attacks on other clustered VMs.The existing system has issues with execution time and false-positive rates.Hence,the overall system performance is degraded considerably.The proposed approach is designed to eliminate Cross-VM side attacks and VM escape and hide the server’s position so that the opponent cannot track the target server beyond a certain point.Every request is passed from source to destination via one broadcast domain to confuse the opponent and avoid them from tracking the server’s position.Allocation of SECURITY Resources accepts a safety game in a simple format as input andfinds the best coverage vector for the opponent using a Stackelberg Equilibrium(SSE)technique.A Mixed Integer Linear Programming(MILP)framework is used in the algorithm.The VM challenge is reduced by afirewall-based controlling mechanism combining behavior-based detection and signature-based virus detection.The pro-posed method is focused on detecting malware attacks effectively and providing better security for the VMs.Finally,the experimental results indicate that the pro-posed security method is efficient.It consumes minimum execution time,better false positive rate,accuracy,and memory usage than the conventional approach.展开更多
Vessels,especially very large or ultra large crude carriers(VLCCs or ULCCs),often can only dock and leave the berth during high tide periods to prevent being stranded.Unfortunately,the current crude scheduling models ...Vessels,especially very large or ultra large crude carriers(VLCCs or ULCCs),often can only dock and leave the berth during high tide periods to prevent being stranded.Unfortunately,the current crude scheduling models do not take into account tidal conditions,which will seriously affect the feasibility of crude schedule.So we first focus on the docking and leaving operations under the tidal actions,and establish a new hybrid continuous-time mixed integer linear programming(MILP)model which incorporates global event based formulation and unit-specific event based formulation.Upon considering that the multiple blending of crude oil can easily cause the production fluctuating,there are some reasonable assumptions that storage tanks can only store pure crude,and charging tanks just can be refilled after being emptied,which helps us obtain a simple MILP model without composition discrepancy caused by crude blending.Two cases are used to demonstrate the efficacy of proposed scheduling model.The results show that the optimization schedule can minimize the demurrage of the vessels and the number of feeding changeovers of crude oil distillation units(CDUs).展开更多
This framework proposes a heuristic algorithm based on LP （linear programming） for optimizing the electricity cost in large residential buildings, in a smart grid environment. Our heuristic tackles large multi-objec...This framework proposes a heuristic algorithm based on LP （linear programming） for optimizing the electricity cost in large residential buildings, in a smart grid environment. Our heuristic tackles large multi-objective energy allocation problem （large number of appliances and high time resolution）. The primary goal is to reduce the electricity bills, and discomfort factor. Also, increase the utilization of domestic renewable energy, and reduce the running time of the optimization algorithm. Our heuristic algorithm uses linear programming relaxation, and two rounding strategies. The first technique, called CR （cumulative rounding）, is designed for thermostatic appliances such as air conditioners and electric heaters, and the second approach, called MCR （minimum cost rounding）, is designed for other interruptible appliances. The results show that the proposed heuristic algorithm can be used to solve large MILP （mixed integer linear programming） problems and gives a decent suboptimal solution in polynomial time.展开更多
This study considers a problem of coordinating production,transportation and sales in a multi-echelon supply chain network.A simulation model is built to generate the random customer demands at different locations,whi...This study considers a problem of coordinating production,transportation and sales in a multi-echelon supply chain network.A simulation model is built to generate the random customer demands at different locations,which are affected by a marketing strategy.Customer demands need to be satisfied by the supply chain through production,transportation and distribution.The optimization problem for coordination of production,trans-portation and distribution is first formulated as a linear programming with demands as input parameters in the constraint.Our objective is to maximize the expectation of the optimal profit of the supply chain given random demands by selecting an optimal marketing strategy.A simulation optimization technique is proposed to con-trol the generation of random demands and solve the linear programming for efficiently learning the optimal marketing strategy.Numerical results show that our method can significantly improve the expected profit of the supply chain and reduce the computational burden of solving linear programming for achieving a given level of probability of correct selection of the optimal marketing strategy.Furthermore,we extend the optimization problem to a mixed integer programming and also demonstrate the computational efficiency of our proposed method.展开更多
Under the background of low-carbon demand, an integrated energy system is the main direction of energy system development. Integrated Energy System (IES) breaks through technical, market and management barriers of tra...Under the background of low-carbon demand, an integrated energy system is the main direction of energy system development. Integrated Energy System (IES) breaks through technical, market and management barriers of traditional energy systems, and it makes unified planning and scheduling for electricity, gas, heat, cold, etc. However, IES contains a variety of energy forms, and those energy forms are coupled with each other. Its planning and operation are challenging problems. Therefore, this paper proposes an IES planning model, which comprehensively considers optimization of the equipment configuration, interconnection of multiple energy stations, renewable energy integration, and optimal operation strategy. During the planning decision-making, planners can use this model to analyze and evaluate the impact of various factors on the planning indicators. Using the proposed model, an IES composed of several buildings in a street block is planned in detail and the effectiveness of the proposed planning model and its solution method is proved. The case study results show the total cost and carbon emission of the model considering both energy station interconnection and RES integration are reduced by 20.2% and 41.5%.展开更多
Mixed integer linear programming(MILP)is an NP-hard problem,which can be solved by the branch and bound algorithm by dividing the original problem into several subproblems and forming a search tree.For each subproblem...Mixed integer linear programming(MILP)is an NP-hard problem,which can be solved by the branch and bound algorithm by dividing the original problem into several subproblems and forming a search tree.For each subproblem,linear programming(LP)relaxation can be solved to find the bound for making the following decisions.Recently,with the increasing dimension of MILPs in different applications,how to accelerate the solution process becomes a huge challenge.In this survey,we summarize techniques and trends to speed up MILP solving from two perspectives.First,we present different approaches in simplex initialization,which can help to accelerate the solution of LP relaxation for each subproblem.Second,we introduce the learning-based technologies in branch and bound algorithms to improve decision making in tree search.We also propose several potential directions and extensions to further enhance the efficiency of solving different MILP problems.展开更多
This study explores the intersection of two pivotal interventions aimed at achieving carbon neutrality:the electric vehicles(EVs)adoption and the renewable energy(RE)electricity generation.Focusing on a Renewable Ener...This study explores the intersection of two pivotal interventions aimed at achieving carbon neutrality:the electric vehicles(EVs)adoption and the renewable energy(RE)electricity generation.Focusing on a Renewable Energy-Dominated(RED)electricity system,the research examines the interdependence between these interventions and their collective impact on economic dispatch.The study's objective is to determine optimal economic dispatch strategies that meet hourly electricity demand,considering two distinct supply scenarios across eight supply options.The first scenario assesses the maximum possible supply,while the second contemplates the minimum possible supply from each option.Additionally,the study delves into the influence of social cost of emissions on these economic dispatches.Employing an experimental design,the study generates representative load curves that incorporate EV charging demands for varied levels of EV penetration,alongside regular electricity demand.Data from Karnataka's RED electricity system provides a basis for the supply-side analysis.The economic dispatch for each supply scenario is formulated as a Mixed Integer Linear Program(MILP),aiming to minimize both costs for generation and social costs of emissions,while adhering to operational constraints of the supply options.Key findings from this approach,highlight several critical insights:the significant role of incorporating social costs in economic dispatch decisions,the tangible impact of EV demand on supply shortages,and the importance of maintaining supply capacity to minimize these shortages.展开更多
To utilize heat and electricity in a clean and integrated manner,a zero-carbon-emission micro Energy Internet(ZCE-MEI) architecture is proposed by incorporating non-supplementary fired compressed air energy storage(NS...To utilize heat and electricity in a clean and integrated manner,a zero-carbon-emission micro Energy Internet(ZCE-MEI) architecture is proposed by incorporating non-supplementary fired compressed air energy storage(NSF-CAES) hub.A typical ZCE-MEI combining power distribution network(PDN) and district heating network(DHN) with NSF-CAES is considered in this paper.NSF-CAES hub is formulated to take the thermal dynamic and pressure behavior into account to enhance dispatch flexibility.A modified Dist Flow model is utilized to allow several discrete and continuous reactive power compensators to maintain voltage quality of PDN.Optimal operation of the ZCE-MEI is firstly modeled as a mixed integer nonlinear programming(MINLP).Several transformations and simplifications are taken to convert the problem as a mixed integer linear programming(MILP)which can be effectively solved by CPLEX.A typical test system composed of a NSF-CAES hub,a 33-bus PDN,and an 8-node DHN is adopted to verify the effectiveness of the proposed ZCE-MEI in terms of reducing operation cost and wind curtailment.展开更多
Large-scale centralized exploitation of intermittent wind energy resources has become popular in many countries.However,as a result of the frequent occurrence of largescale wind curtailment,expansion of corresponding ...Large-scale centralized exploitation of intermittent wind energy resources has become popular in many countries.However,as a result of the frequent occurrence of largescale wind curtailment,expansion of corresponding transmission projects has fallen behind the speed at which installed wind capacity can be developed.In this paper,a coordinated planning approach for a large-scale wind farm integration system and its related regional transmission network is proposed.A bilevel programming model is formulated with the objective of minimizing cost.To reach the global optimum of the bi-level model,this work proposes that the upper-level wind farm integration system planning problem needs to be solved jointly with the lower-level regional transmission planning problem.The bi-level model is expressed in terms of a linearized mathematical problem with equilibrium constraints(MPEC)by Karush-KuhnTucker conditions.It is then solved using mixed integer linear programming solvers.Numerical simulations are conducted to show the validity of the proposed coordinated planning method.展开更多
Distributed generation(DG)is becoming increasingly important due to the serious environmental pollution caused by conventional fossil-energy-based generation and the depletion of non-renewable energy.As the flexible r...Distributed generation(DG)is becoming increasingly important due to the serious environmental pollution caused by conventional fossil-energy-based generation and the depletion of non-renewable energy.As the flexible resources in the active distribution network(ADN),battery energy system(BES)and responsive load(RL)are all able to assist renewable DG integration in day-ahead dispatch.In addition,the security and economic level can be significantly improved by adjusting network topology.Therefore,in this paper,a coordinated day-ahead scheduling method incorporating topology reconfiguration,BES optimization and load response is presented to minimize the total day-ahead operational costs in the ADN.Linearized current injection models are presented for renewable DG,RL and BES based on the linear power flow model,and an extensible linear switching operations calculation(ELSOC)method is proposed to address the network reconfiguration.Thus,a mixed integer linear programming(MILP)model is proposed for optimal coordinated operation of an ADN.The correctness and effectiveness of the proposed method are demonstrated by simulations on a modified test system.In addition,the combined scenario and Monte-Carlo method is used to handle the uncertainties of loads and DGs,and the results of different uncertainties can further verify the feasibility of the proposed model.展开更多
基金Sponsored by Beijing Social Science Foundation of China(14JGC110)Social Science Research Common Program of Beijing Municipal Commission of Education of China(SM201510038011)CUEB Foundation of China(2014XJG005)
文摘Byproduct gas is an important secondary energy in iron and steel industry, and its optimization is vital to cost reduction. With the development of iron and steel industry to be more eco-friendly, it is necessary to construct an integrated optimized system, taking economics, energy consumption and environment into consideration. Therefore, the environmental cost caused by pollutants discharge should be factored in total cost when optimizing byproduct gas distribution. A green mixed integer linear programming （MILP） model for the optimization of byproduct gases was established to reduce total cost, including both operation cost and environmental cost. The operation cost included penalty for gas deviation, costs of fuel and water consumption, holder booster trip penalty, and so forth; while the environmental cost consisted of penalties for both direct and indirect pollutants discharge. Case study showed that the proposed model brought an optimum solution and 2.2% of the total cost could be reduced compared with previous one.
文摘In this study, we aimed to assess the solution quality for location-allocation problems from facilities generated by the software TransCAD®?, a Geographic Information System for Transportation (GIS-T). Such facilities were obtained after using two routines together: Facility Location and Transportation Problem, when compared with optimal solutions from exact mathematical models, based on Mixed Integer Linear Programming (MILP), developed externally for the GIS. The models were applied to three simulations: the first one proposes opening factories and customer allocation in the state of Sao Paulo, Brazil;the second involves a wholesaler and a study of location and allocation of distribution centres for retail customers;and the third one involves the location of day-care centers and allocation of demand (0 - 3 years old children). The results showed that when considering facility capacity, the MILP optimising model presents results up to 37% better than the GIS and proposes different locations to open new facilities.
基金supported by Guangdong Yudean Group Co.LTD,Guangzhou 510630,China.
文摘This paper proposes a deterministic two-stage mixed integer linear programming(TSMILP)approach to solve the reserve constrained dynamic economic dispatch(DED)problem considering valve-point effect(VPE).In stage one,the nonsmooth cost function and the transmission loss are piecewise linearized and consequently the DED problem is formulated as a mixed integer linear programming(MILP)problem,which can be solved by commercial solvers.In stage two,based on the solution obtained in stage one,a range compression technique is proposed to make a further exploitation in the subspace of the whole solution domain.Due to the linear approximation of the transmission loss,the solution obtained in stage two dose not strictly satisfies the power balance constraint.Hence,a forward procedure is employed to eliminate the error.The simulation results on four test systems show that TSMILP makes satisfactory performances,in comparison with the existing methods.
基金Project supported by the National Creative Research Groups Science Foundation of China (No. 60421002)the National "Tenth Five-Year" Science and Technology Research Program of China (No.2004BA204B08)
文摘A novel mixed integer linear programming (NMILP) model for detection of gross errors is presented in this paper. Yamamura et al.(1988) designed a model for detection of gross errors and data reconciliation based on Akaike information cri- terion (AIC). But much computational cost is needed due to its combinational nature. A mixed integer linear programming (MILP) approach was performed to reduce the computational cost and enhance the robustness. But it loses the super performance of maximum likelihood estimation. To reduce the computational cost and have the merit of maximum likelihood estimation, the simultaneous data reconciliation method in an MILP framework is decomposed and replaced by an NMILP subproblem and a quadratic programming (QP) or a least squares estimation (LSE) subproblem. Simulation result of an industrial case shows the high efficiency of the method.
基金Fundamental Research Funds for the Central Universities(2024JBZX038)National Natural Science F oundation of China(62076023)。
文摘The rapid evolution of unmanned aerial vehicle(UAV)technology and autonomous capabilities has positioned UAV as promising last-mile delivery means.Vehicle and onboard UAV collaborative delivery is introduced as a novel delivery mode.Spatiotemporal collaboration,along with energy consumption with payload and wind conditions play important roles in delivery route planning.This paper introduces the traveling salesman problem with time window and onboard UAV(TSPTWOUAV)and emphasizes the consideration of real-world scenarios,focusing on time collaboration and energy consumption with wind and payload.To address this,a mixed integer linear programming(MILP)model is formulated to minimize the energy consumption costs of vehicle and UAV.Furthermore,an adaptive large neighborhood search(ALNS)algorithm is applied to identify high-quality solutions efficiently.The effectiveness of the proposed model and algorithm is validated through numerical tests on real geographic instances and sensitivity analysis of key parameters is conducted.
基金This work was supported in part by the National High Technology Research and Development Program(2012AA 050208)in part by the National Natural Science Foundation of China(51407069)in part by the Fundamental Research Funds for the Central Universities(2014QN02).
文摘In this paper,a mixed integer linear programming(MILP)formulation for robust state estimation(RSE)is proposed.By using the exactly linearized measurement equations instead of the original nonlinear ones,the existingmixed integer nonlinear programming formulation for RSE is converted to a MILP problem.The proposed approach not only guarantees to find the global optimum,but also does not have convergence problems.Simulation results on a rudimentary 3-bus system and several IEEE standard test systems fully illustrate that the proposed methodology is effective with high efficiency.
文摘Finding the accurate solution for N-vehicle exploration problem is NP-hard in strong sense.In this paper,authors build a linear mixed integer programming model for N-vehicle exploration problem based on its properties.The model is then proved equivalent to the original problem.Given the model,one can apply the already existed methods and algorithms for mixed integer linear programming on N-vehicle exploration problem,which helps to enrich methods for solving N-vehicle exploration problem.
文摘Commercial organisations commonly use operational research tools to solve vehicle routing problems. This practice is less commonplace in charity and voluntary organisations. In this paper, we provide an elementary approach for solving the Vehicle Routing Problem (VRP) that we believe can be easily implemented in these types of organisations. The proposed model leverages mixed integer linear programming to optimize the pickup sequence of all customers, each with distinct time windows and locations, transporting them to a final destination using a fleet of vehicles. To ensure ease of implementation, the model utilises Python, a user-friendly programming language, and integrates with the Google Maps API, which simplifies data input by eliminating the need for manual entry of travel times between locations. Troubleshooting methods are incorporated into the model design to ensure easy debugging of the model’s infeasibilities. Additionally, a computation time analysis is conducted to evaluate the efficiency of the code. A node partitioning approach is also discussed, which aims to reduce computational times, especially when handling larger datasets, ensuring this model is realistic and practical for real-world application. By implementing this optimized routing strategy, logistics companies or organisations can expect significant improvements in their day-to-day operations, with minimal computational cost or need for specialised expertise. This includes reduced travel times, minimized fuel consumption, and thus lower operational costs, while ensuring punctuality and meeting the demands of all passengers.
基金funding support provided by the Laurentian University Research Fund for the compilation of this report
文摘Near-surface deposits that extend to considerable depths are often amenable to both open pit mining and/or underground mining.This paper investigates the strategy of mining options for an orebody using a Mixed Integer Linear Programming(MILP)optimization framework.The MILP formulation maximizes the Net Present Value(NPV)of the reserve when extracted with(i)open pit mining,(ii)underground mining,and(iii)concurrent open pit and underground mining.Comparatively,implementing open pit mining generates a higher NPV than underground mining.However considering the investment required for these mining options,underground mining generates a better return on investment than open pit mining.Also,in the concurrent open pit and underground mining scenario,the optimizer prefers extracting blocks using open pit mining.Although the underground mine could access ore sooner,the mining cost differential for open pit mining is more than compensated for by the discounting benefits associated with earlier underground mining.
文摘Cloud computing involves remote server deployments with public net-work infrastructures that allow clients to access computational resources.Virtual Machines(VMs)are supplied on requests and launched without interactions from service providers.Intruders can target these servers and establish malicious con-nections on VMs for carrying out attacks on other clustered VMs.The existing system has issues with execution time and false-positive rates.Hence,the overall system performance is degraded considerably.The proposed approach is designed to eliminate Cross-VM side attacks and VM escape and hide the server’s position so that the opponent cannot track the target server beyond a certain point.Every request is passed from source to destination via one broadcast domain to confuse the opponent and avoid them from tracking the server’s position.Allocation of SECURITY Resources accepts a safety game in a simple format as input andfinds the best coverage vector for the opponent using a Stackelberg Equilibrium(SSE)technique.A Mixed Integer Linear Programming(MILP)framework is used in the algorithm.The VM challenge is reduced by afirewall-based controlling mechanism combining behavior-based detection and signature-based virus detection.The pro-posed method is focused on detecting malware attacks effectively and providing better security for the VMs.Finally,the experimental results indicate that the pro-posed security method is efficient.It consumes minimum execution time,better false positive rate,accuracy,and memory usage than the conventional approach.
文摘Vessels,especially very large or ultra large crude carriers(VLCCs or ULCCs),often can only dock and leave the berth during high tide periods to prevent being stranded.Unfortunately,the current crude scheduling models do not take into account tidal conditions,which will seriously affect the feasibility of crude schedule.So we first focus on the docking and leaving operations under the tidal actions,and establish a new hybrid continuous-time mixed integer linear programming(MILP)model which incorporates global event based formulation and unit-specific event based formulation.Upon considering that the multiple blending of crude oil can easily cause the production fluctuating,there are some reasonable assumptions that storage tanks can only store pure crude,and charging tanks just can be refilled after being emptied,which helps us obtain a simple MILP model without composition discrepancy caused by crude blending.Two cases are used to demonstrate the efficacy of proposed scheduling model.The results show that the optimization schedule can minimize the demurrage of the vessels and the number of feeding changeovers of crude oil distillation units(CDUs).
文摘This framework proposes a heuristic algorithm based on LP （linear programming） for optimizing the electricity cost in large residential buildings, in a smart grid environment. Our heuristic tackles large multi-objective energy allocation problem （large number of appliances and high time resolution）. The primary goal is to reduce the electricity bills, and discomfort factor. Also, increase the utilization of domestic renewable energy, and reduce the running time of the optimization algorithm. Our heuristic algorithm uses linear programming relaxation, and two rounding strategies. The first technique, called CR （cumulative rounding）, is designed for thermostatic appliances such as air conditioners and electric heaters, and the second approach, called MCR （minimum cost rounding）, is designed for other interruptible appliances. The results show that the proposed heuristic algorithm can be used to solve large MILP （mixed integer linear programming） problems and gives a decent suboptimal solution in polynomial time.
基金supported in part by the National Natural Science Foundation of China(72250065,72022001,71901003).
文摘This study considers a problem of coordinating production,transportation and sales in a multi-echelon supply chain network.A simulation model is built to generate the random customer demands at different locations,which are affected by a marketing strategy.Customer demands need to be satisfied by the supply chain through production,transportation and distribution.The optimization problem for coordination of production,trans-portation and distribution is first formulated as a linear programming with demands as input parameters in the constraint.Our objective is to maximize the expectation of the optimal profit of the supply chain given random demands by selecting an optimal marketing strategy.A simulation optimization technique is proposed to con-trol the generation of random demands and solve the linear programming for efficiently learning the optimal marketing strategy.Numerical results show that our method can significantly improve the expected profit of the supply chain and reduce the computational burden of solving linear programming for achieving a given level of probability of correct selection of the optimal marketing strategy.Furthermore,we extend the optimization problem to a mixed integer programming and also demonstrate the computational efficiency of our proposed method.
基金supported by the project of“Sustainable urban power supply through intelligent control and enhanced restoration of AC/DC networks(SUPER)”(52061635104).
文摘Under the background of low-carbon demand, an integrated energy system is the main direction of energy system development. Integrated Energy System (IES) breaks through technical, market and management barriers of traditional energy systems, and it makes unified planning and scheduling for electricity, gas, heat, cold, etc. However, IES contains a variety of energy forms, and those energy forms are coupled with each other. Its planning and operation are challenging problems. Therefore, this paper proposes an IES planning model, which comprehensively considers optimization of the equipment configuration, interconnection of multiple energy stations, renewable energy integration, and optimal operation strategy. During the planning decision-making, planners can use this model to analyze and evaluate the impact of various factors on the planning indicators. Using the proposed model, an IES composed of several buildings in a street block is planned in detail and the effectiveness of the proposed planning model and its solution method is proved. The case study results show the total cost and carbon emission of the model considering both energy station interconnection and RES integration are reduced by 20.2% and 41.5%.
文摘Mixed integer linear programming(MILP)is an NP-hard problem,which can be solved by the branch and bound algorithm by dividing the original problem into several subproblems and forming a search tree.For each subproblem,linear programming(LP)relaxation can be solved to find the bound for making the following decisions.Recently,with the increasing dimension of MILPs in different applications,how to accelerate the solution process becomes a huge challenge.In this survey,we summarize techniques and trends to speed up MILP solving from two perspectives.First,we present different approaches in simplex initialization,which can help to accelerate the solution of LP relaxation for each subproblem.Second,we introduce the learning-based technologies in branch and bound algorithms to improve decision making in tree search.We also propose several potential directions and extensions to further enhance the efficiency of solving different MILP problems.
文摘This study explores the intersection of two pivotal interventions aimed at achieving carbon neutrality:the electric vehicles(EVs)adoption and the renewable energy(RE)electricity generation.Focusing on a Renewable Energy-Dominated(RED)electricity system,the research examines the interdependence between these interventions and their collective impact on economic dispatch.The study's objective is to determine optimal economic dispatch strategies that meet hourly electricity demand,considering two distinct supply scenarios across eight supply options.The first scenario assesses the maximum possible supply,while the second contemplates the minimum possible supply from each option.Additionally,the study delves into the influence of social cost of emissions on these economic dispatches.Employing an experimental design,the study generates representative load curves that incorporate EV charging demands for varied levels of EV penetration,alongside regular electricity demand.Data from Karnataka's RED electricity system provides a basis for the supply-side analysis.The economic dispatch for each supply scenario is formulated as a Mixed Integer Linear Program(MILP),aiming to minimize both costs for generation and social costs of emissions,while adhering to operational constraints of the supply options.Key findings from this approach,highlight several critical insights:the significant role of incorporating social costs in economic dispatch decisions,the tangible impact of EV demand on supply shortages,and the importance of maintaining supply capacity to minimize these shortages.
基金supported in part by the National Natural Science Foundation of China(No.51321005,No.51377092,No.51577163)Opening Foundation of the Qinghai Province Key Laboratory of Photovoltaic Power Generation and Grid-connected Technology
文摘To utilize heat and electricity in a clean and integrated manner,a zero-carbon-emission micro Energy Internet(ZCE-MEI) architecture is proposed by incorporating non-supplementary fired compressed air energy storage(NSF-CAES) hub.A typical ZCE-MEI combining power distribution network(PDN) and district heating network(DHN) with NSF-CAES is considered in this paper.NSF-CAES hub is formulated to take the thermal dynamic and pressure behavior into account to enhance dispatch flexibility.A modified Dist Flow model is utilized to allow several discrete and continuous reactive power compensators to maintain voltage quality of PDN.Optimal operation of the ZCE-MEI is firstly modeled as a mixed integer nonlinear programming(MINLP).Several transformations and simplifications are taken to convert the problem as a mixed integer linear programming(MILP)which can be effectively solved by CPLEX.A typical test system composed of a NSF-CAES hub,a 33-bus PDN,and an 8-node DHN is adopted to verify the effectiveness of the proposed ZCE-MEI in terms of reducing operation cost and wind curtailment.
基金supported in part by the National High Technology Research and Development Program of China(No.2012AA050208)National Natural Science Foundation of China(No.51177043)111 Project(No.B08013).
文摘Large-scale centralized exploitation of intermittent wind energy resources has become popular in many countries.However,as a result of the frequent occurrence of largescale wind curtailment,expansion of corresponding transmission projects has fallen behind the speed at which installed wind capacity can be developed.In this paper,a coordinated planning approach for a large-scale wind farm integration system and its related regional transmission network is proposed.A bilevel programming model is formulated with the objective of minimizing cost.To reach the global optimum of the bi-level model,this work proposes that the upper-level wind farm integration system planning problem needs to be solved jointly with the lower-level regional transmission planning problem.The bi-level model is expressed in terms of a linearized mathematical problem with equilibrium constraints(MPEC)by Karush-KuhnTucker conditions.It is then solved using mixed integer linear programming solvers.Numerical simulations are conducted to show the validity of the proposed coordinated planning method.
基金supported in part by the National Key Research and Development Program of China under Grant No.2016YFB0900100in part by the Key Research and Development Program of Hunan Province of China under Grant No.2018GK2031in part by the Postgraduate Scientific Research Innovation Project of Hunan Province under Grant No.CX20200429.
文摘Distributed generation(DG)is becoming increasingly important due to the serious environmental pollution caused by conventional fossil-energy-based generation and the depletion of non-renewable energy.As the flexible resources in the active distribution network(ADN),battery energy system(BES)and responsive load(RL)are all able to assist renewable DG integration in day-ahead dispatch.In addition,the security and economic level can be significantly improved by adjusting network topology.Therefore,in this paper,a coordinated day-ahead scheduling method incorporating topology reconfiguration,BES optimization and load response is presented to minimize the total day-ahead operational costs in the ADN.Linearized current injection models are presented for renewable DG,RL and BES based on the linear power flow model,and an extensible linear switching operations calculation(ELSOC)method is proposed to address the network reconfiguration.Thus,a mixed integer linear programming(MILP)model is proposed for optimal coordinated operation of an ADN.The correctness and effectiveness of the proposed method are demonstrated by simulations on a modified test system.In addition,the combined scenario and Monte-Carlo method is used to handle the uncertainties of loads and DGs,and the results of different uncertainties can further verify the feasibility of the proposed model.
