Unmanned air vehicles(UAVs) have been regularly employed in modern wars to conduct different missions. Instead of addressing mission planning and route planning separately,this study investigates the issue of joint mi...Unmanned air vehicles(UAVs) have been regularly employed in modern wars to conduct different missions. Instead of addressing mission planning and route planning separately,this study investigates the issue of joint mission and route planning for a fleet of UAVs. The mission planning determines the configuration of weapons in UAVs and the weapons to attack targets, while the route planning determines the UAV’s visiting sequence for the targets. The problem is formulated as an integer linear programming model. Due to the inefficiency of CPLEX on large scale optimization problems, an effective learningbased heuristic, namely, population based adaptive large neighborhood search(P-ALNS), is proposed to solve the model. In P-ALNS, seven neighborhood structures are designed and adaptively utilized in terms of their historical performance. The effectiveness and superiority of the proposed model and algorithm are demonstrated on test instances of small, medium and large sizes. In particular, P-ALNS achieves comparable solutions or as good as those of CPLEX on small-size(20 targets)instances in much shorter time.展开更多
Purpose-Drugs are strategic products with essential functions in human health.An optimum design of the pharmaceutical supply chain is critical to avoid economic damage and adverse effects on human health.The vehicle-r...Purpose-Drugs are strategic products with essential functions in human health.An optimum design of the pharmaceutical supply chain is critical to avoid economic damage and adverse effects on human health.The vehicle-routing problem,focused on finding the lowest-cost routes with available vehicles and constraints,such as time constraints and road length,is an important aspect of this.In this paper,the vehicle routing problem(VRP)for a pharmaceutical company in Turkey is discussed.Design/methodology/approach-A mixed-integer programming(MIP)model based on the vehicle routing problem with time windows(VRPTW)is presented,aiming to minimize the total route cost with certain constraints.As the model provides an optimum solution for small problem sizes with the GUROBI®solver,for large problem sizes,metaheuristic methods that simulate annealing and adaptive large neighborhood search algorithms are proposed.A real dataset was used to analyze the effectiveness of the metaheuristic algorithms.The proposed simulated annealing(SA)and adaptive large neighborhood search(ALNS)were evaluated and compared against GUROBI®and each other through a set of real problem instances.Findings-The model is solved optimally for a small-sized dataset with exact algorithms;for solving a larger dataset,however,metaheuristic algorithms require significantly lesser time.For the problem addressed in this study,while the metaheuristic algorithms obtained the optimum solution in less than one minute,the solution in the GUROBI®solver was limited to one hour and three hours,and no solution could be obtained in this time interval.Originality/value-The VRPTW problem presented in this paper is a real-life problem.The vehicle fleet owned by the factory cannot be transported between certain suppliers,which complicates the solution of the problem.展开更多
基金supportes by the National Nature Science Foundation o f China (71771215,62122093)。
文摘Unmanned air vehicles(UAVs) have been regularly employed in modern wars to conduct different missions. Instead of addressing mission planning and route planning separately,this study investigates the issue of joint mission and route planning for a fleet of UAVs. The mission planning determines the configuration of weapons in UAVs and the weapons to attack targets, while the route planning determines the UAV’s visiting sequence for the targets. The problem is formulated as an integer linear programming model. Due to the inefficiency of CPLEX on large scale optimization problems, an effective learningbased heuristic, namely, population based adaptive large neighborhood search(P-ALNS), is proposed to solve the model. In P-ALNS, seven neighborhood structures are designed and adaptively utilized in terms of their historical performance. The effectiveness and superiority of the proposed model and algorithm are demonstrated on test instances of small, medium and large sizes. In particular, P-ALNS achieves comparable solutions or as good as those of CPLEX on small-size(20 targets)instances in much shorter time.
文摘Purpose-Drugs are strategic products with essential functions in human health.An optimum design of the pharmaceutical supply chain is critical to avoid economic damage and adverse effects on human health.The vehicle-routing problem,focused on finding the lowest-cost routes with available vehicles and constraints,such as time constraints and road length,is an important aspect of this.In this paper,the vehicle routing problem(VRP)for a pharmaceutical company in Turkey is discussed.Design/methodology/approach-A mixed-integer programming(MIP)model based on the vehicle routing problem with time windows(VRPTW)is presented,aiming to minimize the total route cost with certain constraints.As the model provides an optimum solution for small problem sizes with the GUROBI®solver,for large problem sizes,metaheuristic methods that simulate annealing and adaptive large neighborhood search algorithms are proposed.A real dataset was used to analyze the effectiveness of the metaheuristic algorithms.The proposed simulated annealing(SA)and adaptive large neighborhood search(ALNS)were evaluated and compared against GUROBI®and each other through a set of real problem instances.Findings-The model is solved optimally for a small-sized dataset with exact algorithms;for solving a larger dataset,however,metaheuristic algorithms require significantly lesser time.For the problem addressed in this study,while the metaheuristic algorithms obtained the optimum solution in less than one minute,the solution in the GUROBI®solver was limited to one hour and three hours,and no solution could be obtained in this time interval.Originality/value-The VRPTW problem presented in this paper is a real-life problem.The vehicle fleet owned by the factory cannot be transported between certain suppliers,which complicates the solution of the problem.
