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

被引:49
|
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
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