Bi-objective reentrant hybrid flowshop scheduling: an iterated Pareto greedy algorithm

被引:52
作者
Ying, Kuo-Ching [1 ]
Lin, Shih-Wei [2 ]
Wan, Shu-Yen [2 ]
机构
[1] Natl Taipei Univ Technol, Dept Ind Engn & Management, Taipei 106, Taiwan
[2] Chang Gung Univ, Dept Informat Management, Taoyuan, Taiwan
关键词
scheduling; reentrant hybrid flowshop; bi-objective; meta-heuristic; DEPENDENT SETUP TIMES; MINIMIZING MAKESPAN; GENETIC ALGORITHM; PARALLEL MACHINES; SHOP; TARDINESS; SEARCH; DATES;
D O I
10.1080/00207543.2014.910627
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
The multi-objective reentrant hybrid flowshop scheduling problem (RHFSP) exhibits significance in many industrial applications, but appears under-studied in the literature. In this study, an iterated Pareto greedy (IPG) algorithm is proposed to solve a RHFSP with the bi-objective of minimising makespan and total tardiness. The performance of the proposed IPG algorithm is evaluated by comparing its solutions to existing meta-heuristic algorithms on the same benchmark problem set. Experimental results show that the proposed IPG algorithm significantly outperforms the best available algorithms in terms of the convergence to optimal solutions, the diversity of solutions and the dominance of solutions. The statistical analysis manifestly shows that the proposed IPG algorithm can serve as a new benchmark approach for future research on this extremely challenging scheduling problem.
引用
收藏
页码:5735 / 5747
页数:13
相关论文
共 34 条
[1]   A genetic algorithm for an industrial multiprocessor flow shop scheduling problem with recirculation [J].
Bertel, S ;
Billaut, JC .
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2004, 159 (03) :651-662
[2]   Re-entrant flow shop scheduling problem with time windows using hybrid genetic algorithm based on auto-tuning strategy [J].
Chamnanlor, Chettha ;
Sethanan, Kanchana ;
Chien, Chen-Fu ;
Gen, Mitsuo .
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH, 2014, 52 (09) :2612-2629
[3]   Hybrid Genetic Algorithms for Solving Reentrant Flow-Shop Scheduling with Time Windows [J].
Chamnanlor, Chettha ;
Sethanan, Kanchana ;
Chien, Chen-Fu ;
Gen, Mitsuo .
INDUSTRIAL ENGINEERING AND MANAGEMENT SYSTEMS, 2013, 12 (04) :306-316
[4]  
Chen C. L., 2012, ACAI 2012 INT C AUT, P1065
[5]   Bi-objective scheduling for reentrant hybrid flow shop using Pareto genetic algorithm [J].
Cho, Hang-Min ;
Bae, Suk-Joo ;
Kim, Jungwuk ;
Jeong, In-Jae .
COMPUTERS & INDUSTRIAL ENGINEERING, 2011, 61 (03) :529-541
[6]   Scheduling algorithms for two-stage reentrant hybrid flow shops: minimizing makespan under the maximum allowable due dates [J].
Choi, Hyun-Seon ;
Kim, Hyung-Won ;
Lee, Dong-Ho ;
Yoon, Junggee ;
Yun, Chang Yeon ;
Chae, Kevin B. .
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, 2009, 42 (9-10) :963-973
[7]   Minimizing total tardiness of orders with reentrant lots in a hybrid flowshop [J].
Choi, SW ;
Kim, YD ;
Lee, GC .
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH, 2005, 43 (11) :2149-2167
[8]   Multi-objective sequence dependent setup times permutation flowshop: A new algorithm and a comprehensive study [J].
Ciavotta, Michele ;
Minella, Gerardo ;
Ruiz, Ruben .
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2013, 227 (02) :301-313
[9]   A fast and elitist multiobjective genetic algorithm: NSGA-II [J].
Deb, K ;
Pratap, A ;
Agarwal, S ;
Meyarivan, T .
IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION, 2002, 6 (02) :182-197
[10]   New multi-objective method to solve reentrant hybrid flow shop scheduling problem [J].
Dugardin, Frederic ;
Yalaoui, Farouk ;
Amodeo, Lionel .
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2010, 203 (01) :22-31