Paper Info
Title
A Novel Quantum Immune Algorithm For Multiobjective Flexible Job Shop Scheduling
Abstract
In this study, a hybrid of Quantum Evolutionary and Artificial Immune Algorithms (QIA) is proposed for solving Multiobjective Flexible Job Shop Scheduling Problem (MFJSSP). This problem is formulated as three-objective problem which minimizes completion time (makespan), critical machine workload and total work load of all machines. The quantum coding is shown to improve the immune strategy. The proposed algorithm overcomes the problem by increasing the speed of convergence and diversity of population. Three benchmarks of Kacem and Brandimart are examined to evaluate the performance of the proposed algorithm. The experimental results show a better performance in comparison to other approaches.
Year
DOI
Venue
2014
10.1142/S0218213014500067
INTERNATIONAL JOURNAL ON ARTIFICIAL INTELLIGENCE TOOLS
Keywords
Field
DocType
Flexible job shop scheduling, immune algorithm (IA), quantum evolutionary algorithm
Convergence (routing),Quantum,Population,Mathematical optimization,Job shop scheduling,Computer science,Workload,Flow shop scheduling,Algorithm,Coding (social sciences),Rate-monotonic scheduling
Journal
Volume
Issue
ISSN
23
5
0218-2130
Citations 
PageRank 
References 
0
0.34
8
Authors
2
Name
Order
Citations
PageRank
Zohreh Davarzani100.34
Mohammad R. Akbarzadeh-Totonchi212518.26