Improved Estimation of Distribution Algorithm for Solving Unrelated Parallel Machine Scheduling Problem  

作　　者：孙泽文 顾幸生 

机构地区：[1]Key Laboratory of Advanced Control and Optimization for Chemical Process,Ministry of Education,East China University of Science and Technology

出　　处：《Journal of Donghua University(English Edition)》2016年第5期797-802,共6页东华大学学报（英文版）

基　　金：National Natural Science Foundations of China(Nos.61573144,61174040)

摘　　要：Scheduling problem is a well-known combinatorial optimization problem.An effective improved estimation of distribution algorithm(IEDA) was proposed for minimizing the makespan of the unrelated parallel machine scheduling problem(UPMSP).Mathematical description was given for the UPMSP.The IEDA which was combined with variable neighborhood search(IEDA_VNS) was proposed to solve the UPMSP in order to improve local search ability.A new encoding method was designed for representing the feasible solutions of the UPMSP.More knowledge of the UPMSP were taken consideration in IEDA_ VNS for probability matrix which was based the processing time matrix.The simulation results show that the proposed IEDA_VNS can solve the problem effectively.Scheduling problem is a well-known combinatorial optimization problem.An effective improved estimation of distribution algorithm（IEDA） was proposed for minimizing the makespan of the unrelated parallel machine scheduling problem（UPMSP）.Mathematical description was given for the UPMSP.The IEDA which was combined with variable neighborhood search（IEDA_VNS） was proposed to solve the UPMSP in order to improve local search ability.A new encoding method was designed for representing the feasible solutions of the UPMSP.More knowledge of the UPMSP were taken consideration in IEDA_ VNS for probability matrix which was based the processing time matrix.The simulation results show that the proposed IEDA_VNS can solve the problem effectively.

关 键 词：Scheduling neighborhood scheduling minimizing processed unrelated probabilistic intelligent heuristic representing 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]