Artificial bee colony algorithm for scheduling and rescheduling fuzzy flexible job shop problem with new job insertion

详细信息    查看全文

• 作者：Kai Zhou Gao^a ; ^b ; Ponnuthurai Nagaratnam Suganthan^b ; Quan Ke Pan^c ; ^{panquanke@qq.com" class="auth_mail" title="E-mail the corresponding author} ; Mehmet Fatih Tasgetiren^d ; Ali Sadollah^b
• 关键词：Artificial bee colony ; Flexible job shop scheduling ; Fuzzy processing time ; New job insertion ; Remanufacturing.
• 刊名：Knowledge-Based Systems
• 出版年：2016
• 出版时间：1 October 2016
• 年：2016
• 卷：109
• 期：Complete
• 页码：1-16
• 全文大小：5030 K

文摘

This study addresses flexible job shop scheduling problem (FJSP) with two constraints, namely fuzzy processing time and new job insertion. The uncertainty of processing time and new job insertion are two scheduling related characteristics in remanufacturing. Fuzzy processing time is used to describe the uncertainty in processing time. Rescheduling operator is executed when new job(s) is (are) inserted into the schedule currently being executed. A two-stage artificial bee colony (TABC) algorithm with several improvements is proposed to solve FJSP with fuzzy processing time and new job insertion constraints. Also, several new solution generation methods and improvement strategies are proposed and compared with each other. The objective is to minimize maximum fuzzy completion time. Eight instances from remanufacturing are solved using the proposed TABC algorithm. The proposed improvement strategies are compared and discussed in detail. Two proposed ABC algorithms with the best performances are compared against seven existing algorithms over by five benchmark cases. The optimization results and comparisons show the competitiveness of the proposed TABC algorithm for solving FJSP.