Multi-objective Optimization of the Distributed Permutation Flow Shop Scheduling Problem with Transportation and Eligibility Constraints  

作　　者：Shuang Cai Ke Yang Ke Liu 

机构地区：[1]Academy of Mathematics and Systems Science,Chinese Academy of Sciences,Beijing 100190,China [2]University of Chinese Academy of Sciences,Beijing 100049,China [3]Key Laboratory of Management,Decision and Information Systems,Chinese Academy of Sciences,Beijing 100190,China [4]National Center for Mathematics and Interdisciplinary Sciences,Chinese Academy of Sciences,Beijing 100190,China

出　　处：《Journal of the Operations Research Society of China》2018年第3期391-416,共26页中国运筹学会会刊（英文）

基　　金：This research was partially supported by the National Natural Science Foundation of China(Nos.71390334 and 11271356).

摘　　要：In this paper,we consider the distributed permutation flow shop scheduling problem(DPFSSP)with transportation and eligibility constrains.Three objectives are taken into account,i.e.,makespan,maximum lateness and total costs(transportation costs and setup costs).To the best of our knowledge,there is no published work on multi-objective optimization of the DPFSSP with transportation and eligibility constraints.First,we present the mathematics model and constructive heuristics for single objective;then,we propose an improved The Nondominated Sorting Genetic Algorithm II(NSGA-II)for the multi-objective DPFSSP to find Pareto optimal solutions,in which a novel solution representation,a new population re-/initialization,effective crossover and mutation operators,as well as local search methods are developed.Based on extensive computational and statistical experiments,the proposed algorithm performs better than the well-known NSGA-II and the Strength Pareto Evolutionary Algorithm 2(SPEA2).

关 键 词：Multi-objective optimization Distributed scheduling Permutation flow shop scheduling TRANSPORTATION NSGA-II 

分 类 号：O17[理学—数学]