A two-stage artificial bee colony algorithm scheduling flexible job-shop scheduling problem with new job insertion

被引:185
|
作者
Gao, Kai Zhou [1 ]
Suganthan, Ponnuthurai Nagaratnam [1 ]
Chua, Tay Jin [2 ]
Chong, Chin Soon [2 ]
Cai, Tian Xiang [2 ]
Pan, Qan Ke [3 ]
机构
[1] Nanyang Technol Univ, Sch Elect & Elect Engn, Singapore 639798, Singapore
[2] Singapore Inst Mfg Technol, Singapore 638075, Singapore
[3] Huazhong Univ Sci & Technol, State Key Lab Digital Mfg Equipment & Technol, Wuhan 430074, Peoples R China
基金
美国国家科学基金会;
关键词
Flexible job-shop scheduling; New job inserting; Artificial bee colony; Re-scheduling; OPTIMIZATION;
D O I
10.1016/j.eswa.2015.06.004
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This study addresses the scheduling problem in remanufacturing engineering. The purpose of this paper is to model effectively to solve remanufacturing scheduling problem. The problem is modeled as flexible job-shop scheduling problem (FISP) and is divided into two stages: scheduling and re-scheduling when new job arrives. The uncertainty in timing of returns in remanufacturing is modeled as new job inserting constraint in FJSP. A two-stage artificial bee colony (TABC) algorithm is proposed for scheduling and re-scheduling with new job(s) inserting. The objective is to minimize makespan (maximum complete time). A new rule is proposed to initialize bee colony population. An ensemble local search is proposed to improve algorithm performance. Three re-scheduling strategies are proposed and compared. Extensive computational experiments are carried out using fifteen well-known benchmark instances with eight instances from remanufacturing. Forscheduling performance, TABC is compared to five existing algorithms. For re-scheduling performance, TABC is compared to six simple heuristics and proposed hybrid heuristics. The results and comparisons show that TABC is effective in both scheduling stage and rescheduling stage. (C) 2015 Elsevier Ltd. All rights reserved.
引用
收藏
页码:7652 / 7663
页数:12
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