Paper Info
Title
Solving multi-objective fuzzy flexible job shop scheduling problem using MABC algorithm.
Abstract
A new artificial bee colony algorithm called modified artificial bee colony algorithm (MABC) is presented to solve the multi-objective fuzzy flexible job-shop scheduling problem (MFFJSP) in this paper. The objectives of MFFJSP are to minimize the maximum fuzzy completion time (fuzzy makespan), maximize the weighted agreement index and minimize the maximum fuzzy machine workload. The three-point satisfaction-degree model is adopted to calculate the agreement index and this model can indicate the degree of satisfaction between the due date and the processing time. An effective local search operator based on variable neighborhood search (VNS) and crossover operator are embedded in this algorithm for obtaining good searching performance. In order to make the novel algorithm valid, we texted it, five benchmark instances and a practical case for the sake of effectiveness. Then, the performance of the proposed MABC has been compared with other existing algorithms to prove the superiority of this algorithm. In the end, the Taguchi method is used to investigate the impact of three key parameters from the MABC.
Year
DOI
Venue
2019
10.3233/JIFS-181152
JOURNAL OF INTELLIGENT & FUZZY SYSTEMS
Keywords
Field
DocType
Artificial bee colony algorithm,agreement index,variable neighborhood search,multi-objective fuzzy flexible job-shop scheduling problem
Job shop scheduling problem,Fuzzy logic,Artificial intelligence,Mathematics,Machine learning
Journal
Volume
Issue
ISSN
36
2
1064-1246
Citations 
PageRank 
References 
0
0.34
12
Authors
3
Name
Order
Citations
PageRank
Yuguang Zhong132.08
Yang Fan200.34
Feng Liu34610.34