Resource-constrained project scheduling problem（RCPSP） is an important problem in research on project management. But there has been little attention paid to the objective of minimizing activities＇ cost with the re...Resource-constrained project scheduling problem（RCPSP） is an important problem in research on project management. But there has been little attention paid to the objective of minimizing activities＇ cost with the resource constraints that is a critical sub-problem in partner selection of construction supply chain management because the capacities of the renewable resources supplied by the partners will effect on the project scheduling. Its mathematic model is presented firstly, and analysis on the characteristic of the problem shows that the objective function is non-regular and the problem is NP-complete following which the basic idea for solution is clarified. Based on a definition of preposing activity cost matrix, a heuristic algorithm is brought forward. Analyses on the complexity of the heuristics and the result of numerical studies show that the heuristic algorithm is feasible and relatively effective.展开更多
Multi-bridge machining systems(MBMS) have gained wide applications in industry due to their high production capacity and efficiency. They contain multiple bridge machines working in parallel within their partially ove...Multi-bridge machining systems(MBMS) have gained wide applications in industry due to their high production capacity and efficiency. They contain multiple bridge machines working in parallel within their partially overlapping workspaces.Their scheduling problems can be abstracted into a serial-colored travelling salesman problem in which each salesman has some exclusive cities and some cities shared with its neighbor(s). To solve it, we develop a greedy algorithm that selects a neighboring city satisfying proximity. The algorithm allows a salesman to select randomly its shared cities and runs accordingly many times. It can thus be used to solve job scheduling problems for MBMS. Subsequently, a collision-free scheduling method is proposed to address both job scheduling and collision resolution issues of MBMS. It is an extension of the greedy algorithm by introducing time window constraints and a collision resolution mechanism. Thus, the augmented greedy algorithm can try its best to select stepwise a job for an individual machine such that no time overlaps exist between it and the job sequence of the neighboring machine dealt in the corresponding overlapping workspace; and remove such a time overlap only when it is inevitable. Finally, we conduct a case study of a large triplebridge waterjet cutting system by applying the proposed method.展开更多
This research focuses on the home health care optimization problem that involves staff routing and scheduling problems.The considered problem is an extension of multiple travelling salesman problem.It consists of find...This research focuses on the home health care optimization problem that involves staff routing and scheduling problems.The considered problem is an extension of multiple travelling salesman problem.It consists of finding the shortest path for a set of caregivers visiting a set of patients at their homes in order to perform various tasks during a given horizon.Thus,a mixed-integer linear programming model is proposed to minimize the overall service time performed by all caregivers while respecting the workload balancing constraint.Nevertheless,when the time horizon become large,practical-sized instances become very difficult to solve in a reasonable computational time.Therefore,a new Learning Genetic Algorithm for mTSP(LGA-mTSP)is proposed to solve the problem.LGA-mTSP is composed of a new genetic algorithm for mTSP,combined with a learning approach,called learning curves.Learning refers to that caregivers’productivity increases as they gain more experience.Learning curves approach is considered as a way to save time and costs.Simulation results show the efficiency of the proposed approach and the impact of learning curve strategy to reduce service times.展开更多
With the challenge of great growing of transport diversity for the automobile enterprises, the heterogeneous vehicle routing problem with multiple depots, multiple types of finished vehicles and multiple types of tran...With the challenge of great growing of transport diversity for the automobile enterprises, the heterogeneous vehicle routing problem with multiple depots, multiple types of finished vehicles and multiple types of transport vehicles in finished vehicle logistics(HVRPMD) is modelled and solved. A multi-objective optimization model for HVRPMD is presented considering loading constraints to minimize the total cost and minimize the number of transport vehicles. Then a hybrid heuristic algorithm based on genetic algorithm and particle swarm optimization(GA-PSO) is developed. Moreover, a case study is used to evaluate the effectiveness of this algorithm. By comparing the GA-PSO algorithm with the traditional GA algorithm, the simulation results demonstrate the proposed GA-PSO algorithm is able to better support the HVRPMD problem in practice. Contributions of the paper are the modelling and solving of a complex HVRPMD in logistics industry.展开更多
The airplane refueling problem can be stated as follows.We are given n airplanes which can refuel one another during the flight.Each airplane has a reservoir volume wj(liters)and a consumption rate pj(liters per kilom...The airplane refueling problem can be stated as follows.We are given n airplanes which can refuel one another during the flight.Each airplane has a reservoir volume wj(liters)and a consumption rate pj(liters per kilometer).As soon as one airplane runs out of fuel,it is dropping out of the flight.The problem asks for finding a refueling scheme such that the last plane in the air reach a maximal distance.An equivalent version is the n-vehicle exploration problem.The computational complexity of this non-linear combinatorial optimization problem is open so far.This paper employs the neighborhood exchange method of single-machine scheduling to study the precedence relations of jobs,so as to improve the necessary and sufficiency conditions of optimal solutions,and establish an efficient heuristic algorithm which is a generalization of several existing special algorithms.展开更多
文摘Resource-constrained project scheduling problem（RCPSP） is an important problem in research on project management. But there has been little attention paid to the objective of minimizing activities＇ cost with the resource constraints that is a critical sub-problem in partner selection of construction supply chain management because the capacities of the renewable resources supplied by the partners will effect on the project scheduling. Its mathematic model is presented firstly, and analysis on the characteristic of the problem shows that the objective function is non-regular and the problem is NP-complete following which the basic idea for solution is clarified. Based on a definition of preposing activity cost matrix, a heuristic algorithm is brought forward. Analyses on the complexity of the heuristics and the result of numerical studies show that the heuristic algorithm is feasible and relatively effective.
基金supported in part by the National Natural Science Foundation of China(61773115,61374069,61374148)the Natural Science Foundation of Jiangsu Province(BK20161427)
文摘Multi-bridge machining systems(MBMS) have gained wide applications in industry due to their high production capacity and efficiency. They contain multiple bridge machines working in parallel within their partially overlapping workspaces.Their scheduling problems can be abstracted into a serial-colored travelling salesman problem in which each salesman has some exclusive cities and some cities shared with its neighbor(s). To solve it, we develop a greedy algorithm that selects a neighboring city satisfying proximity. The algorithm allows a salesman to select randomly its shared cities and runs accordingly many times. It can thus be used to solve job scheduling problems for MBMS. Subsequently, a collision-free scheduling method is proposed to address both job scheduling and collision resolution issues of MBMS. It is an extension of the greedy algorithm by introducing time window constraints and a collision resolution mechanism. Thus, the augmented greedy algorithm can try its best to select stepwise a job for an individual machine such that no time overlaps exist between it and the job sequence of the neighboring machine dealt in the corresponding overlapping workspace; and remove such a time overlap only when it is inevitable. Finally, we conduct a case study of a large triplebridge waterjet cutting system by applying the proposed method.
基金Supported by National Natural Science Foundation of China(60474058,60604026)National High Technology Research and Development Program of China(863 Program)(2007AA04Z156)
文摘This research focuses on the home health care optimization problem that involves staff routing and scheduling problems.The considered problem is an extension of multiple travelling salesman problem.It consists of finding the shortest path for a set of caregivers visiting a set of patients at their homes in order to perform various tasks during a given horizon.Thus,a mixed-integer linear programming model is proposed to minimize the overall service time performed by all caregivers while respecting the workload balancing constraint.Nevertheless,when the time horizon become large,practical-sized instances become very difficult to solve in a reasonable computational time.Therefore,a new Learning Genetic Algorithm for mTSP(LGA-mTSP)is proposed to solve the problem.LGA-mTSP is composed of a new genetic algorithm for mTSP,combined with a learning approach,called learning curves.Learning refers to that caregivers’productivity increases as they gain more experience.Learning curves approach is considered as a way to save time and costs.Simulation results show the efficiency of the proposed approach and the impact of learning curve strategy to reduce service times.
基金Supported by the National Natural Science Foundation of China(No.51565036)。
文摘With the challenge of great growing of transport diversity for the automobile enterprises, the heterogeneous vehicle routing problem with multiple depots, multiple types of finished vehicles and multiple types of transport vehicles in finished vehicle logistics(HVRPMD) is modelled and solved. A multi-objective optimization model for HVRPMD is presented considering loading constraints to minimize the total cost and minimize the number of transport vehicles. Then a hybrid heuristic algorithm based on genetic algorithm and particle swarm optimization(GA-PSO) is developed. Moreover, a case study is used to evaluate the effectiveness of this algorithm. By comparing the GA-PSO algorithm with the traditional GA algorithm, the simulation results demonstrate the proposed GA-PSO algorithm is able to better support the HVRPMD problem in practice. Contributions of the paper are the modelling and solving of a complex HVRPMD in logistics industry.
基金Supported by Natural Science Foundation of Henan Province(Grant Nos.232300421218 and 252300421483).
文摘The airplane refueling problem can be stated as follows.We are given n airplanes which can refuel one another during the flight.Each airplane has a reservoir volume wj(liters)and a consumption rate pj(liters per kilometer).As soon as one airplane runs out of fuel,it is dropping out of the flight.The problem asks for finding a refueling scheme such that the last plane in the air reach a maximal distance.An equivalent version is the n-vehicle exploration problem.The computational complexity of this non-linear combinatorial optimization problem is open so far.This paper employs the neighborhood exchange method of single-machine scheduling to study the precedence relations of jobs,so as to improve the necessary and sufficiency conditions of optimal solutions,and establish an efficient heuristic algorithm which is a generalization of several existing special algorithms.
