Multiobjective decomposition-based Mallows Models estimation of distribution algorithm. A case of study for permutation flowshop scheduling problem

作     者：Zangari, Murilo Mendiburu, Alexander Santana, Roberto Pozo, Aurora 

作者机构：Univ Fed Parana UFPR Comp Sci Dept PO 19081 BR-81531970 Curitiba Parana Brazil Univ Basque Country UPV EHU Dept Comp Architecture & Technol Intelligent Syst Grp Paseo Manuel Lardizabal 1 San Sebastian 20080 Guipuzcoa Spain Univ Basque Country UPV EHU Dept Comp Sci & Artificial Intelligence Intelligent Syst Grp Paseo Manuel Lardizabal 1 San Sebastian 20080 Guipuzcoa Spain 

出 版 物：《INFORMATION SCIENCES》 (信息科学)

年 卷 期：2017年第397卷

页      面：137-154页

核心收录：

学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：CNPq [306103/2015-0, 400125/2014-5] CAPES (Brazil Government) Basque Government [IT-609-13] Spanish Ministry of Economy, Industry and Competitiveness [TIN2016-78365-R] 

主　　题：Estimation of distribution algorithm Mallows models Multi-objective optimization Decomposition-based Permutation optimization problems Flowshop scheduling problem 

摘      要：Estimation of distribution algorithms (EDAs) have become a reliable alternative to solve a broad range of single and multi-objective optimization problems. Recently, distance-based exponential models, such as Mallows Model (MM) and Generalized Mallows Model (GMM), have demonstrated their validity in the context of EDAs to deal with permutation-based optimization problems. The aim of this paper is two-fold. First, we introduce a novel general multi-objective decomposition-based EDA using Kernels of Mallows models (MEDA/D-MK framework) for solving multi-objective permutation-based optimization problems. Second, in order to demonstrate the validity of the MEDA/D-MK, we have applied it to solve the multi-objective permutation flowshop scheduling problem (MoPFSP) minimizing the total flow time and the makespan. The permutation flowshop scheduling problem is one of the most studied problems of this kind due to its fields of application and algorithmic challenge. The results of our experiments show that MEDA/D-MK outperforms an improved MOEA/D variant specific tailored for minimizing makespan and total flowtime. Furthermore, our approach achieves competitive results compared to the best-known approximated Pareto fronts reported in the literature for the benchmark considered. (C) 2017 Elsevier Inc. All rights reserved.