4.7 Article

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

期刊

KNOWLEDGE-BASED SYSTEMS
卷 109, 期 -, 页码 1-16

出版社

ELSEVIER SCIENCE BV
DOI: 10.1016/j.knosys.2016.06.014

关键词

Artificial bee colony; Flexible job shop scheduling; Fuzzy processing time; New job insertion; Remanufacturing

资金

  1. National Natural Science Foundation of China [51575212, 61503170]
  2. Program for New Century Excellent Talents in University [NCET-13-0106]
  3. Science Foundation of Hubei Province in China [2015CFB560]
  4. Specialized Research Fund for the Doctoral Program of Higher Education [20130042110035]
  5. Key Laboratory Basic Research Foundation of Education Department of Liaoning Province [LZ2014014]

向作者/读者索取更多资源

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. (C) 2016 Elsevier B.V. All rights reserved.

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