Automatic Algorithm Design for Hybrid Flowshop Scheduling Problems

被引:27
作者
Alfaro-Fernandez, Pedro [1 ]
Ruiz, Ruben [1 ]
Pagnozzi, Federico [2 ]
Stutzle, Thomas [2 ]
机构
[1] Univ Politecn Valencia, Grp Sistemas Optimizat Aplicada, Inst Tecnol Informat, Ciudad Politecn Innovat, Edif 8G,Acc B Camino de Vera S-N, Valencia 46021, Spain
[2] Univ Libre Bruxelles, IRIDIA, CP 194-6,Av F Roosevelt 50, B-1050 Brussels, Belgium
关键词
Scheduling; Hybrid flowshop; Automatic algorithm configuration; Automatic Algorithm Design; ITERATED GREEDY ALGORITHM; SEARCH ALGORITHM; OPTIMIZATION; PARALLEL; FLOWTIME;
D O I
10.1016/j.ejor.2019.10.004
中图分类号
C93 [管理学];
学科分类号
12 ; 1201 ; 1202 ; 120202 ;
摘要
Industrial production scheduling problems are challenges that researchers have been trying to solve for decades. Many practical scheduling problems such as the hybrid flowshop are ATP-hard. As a result, researchers resort to metaheuristics to obtain effective and efficient solutions. The traditional design process of metaheuristics is mainly manual, often metaphor-based, biased by previous experience and prone to producing overly tailored methods that only work well on the tested problems and objectives. In this paper, we use an Automatic Algorithm Design (AAD) methodology to eliminate these limitations. AAD is capable of composing algorithms from components with minimal human intervention. We test the proposed MD for three different optimization objectives in the hybrid flowshop. Comprehensive computational and statistical testing demonstrates that automatically designed algorithms outperform specifically tailored state-of-the-art methods for the tested objectives in most cases. (C) 2019 Elsevier B.V. All rights reserved.
引用
收藏
页码:835 / 845
页数:11
相关论文
共 48 条
[31]  
Marichelvam M. K., 2013, International Journal of Logistics Economics and Globalisation, V5, P15
[32]   A Discrete Firefly Algorithm for the Multi-Objective Hybrid Flowshop Scheduling Problems [J].
Marichelvam, Mariappan Kadarkarainadar ;
Prabaharan, Thirumoorthy ;
Yang, Xin She .
IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION, 2014, 18 (02) :301-305
[33]  
Marmion Marie-Eleonore, 2013, Hybrid Metaheuristics. 8th International Workshop, HM 2013. Proceedings, P144, DOI 10.1007/978-3-642-38516-2_12
[34]   Grammar-based generation of stochastic local search heuristics through automatic algorithm configuration tools [J].
Mascia, Franco ;
Lopez-Ibanez, Manuel ;
Dubois-Lacoste, Jeremie ;
Stutzle, Thomas .
COMPUTERS & OPERATIONS RESEARCH, 2014, 51 :190-199
[35]  
Montgomery D.C., 2017, Design and Analysis of Experiments
[36]   A HEURISTIC ALGORITHM FOR THE M-MACHINE, N-JOB FLOWSHOP SEQUENCING PROBLEM [J].
NAWAZ, M ;
ENSCORE, EE ;
HAM, I .
OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE, 1983, 11 (01) :91-95
[37]   Iterated search methods for earliness and tardiness minimization in hybrid flowshops with due windows [J].
Pan, Quan-Ke ;
Ruiz, Ruben ;
Alfaro-Fernandez, Pedro .
COMPUTERS & OPERATIONS RESEARCH, 2017, 80 :50-60
[38]   An improved migrating birds optimisation for a hybrid flowshop scheduling with total flowtime minimisation [J].
Pan, Quan-Ke ;
Dong, Yan .
INFORMATION SCIENCES, 2014, 277 :643-655
[39]   A novel discrete artificial bee colony algorithm for the hybrid flowshop scheduling problem with makespan minimisation [J].
Pan, Quan-Ke ;
Wang, Ling ;
Li, Jun-Qing ;
Duan, Jun-Hua .
OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE, 2014, 45 :42-56
[40]   An efficient heuristic for scheduling in a flowshop to minimize total weighted flowtime of jobs [J].
Rajendran, C ;
Ziegler, H .
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 1997, 103 (01) :129-138