A Novel Quantum Immune Algorithm for Multiobjective Flexible Job Shop Scheduling

作     者：Davarzani, Zohreh Akbarzadeh-T, Mohammad-R. 

作者机构：Payame Noor Univ Dept Comp Engn Tehran 193954697 Iran Ferdowsi Univ Mashhad Ctr Excellence Soft Comp & Intelligent Informat P Dept Elect & Comp Engn Mashhad Iran 

出 版 物：《INTERNATIONAL JOURNAL ON ARTIFICIAL INTELLIGENCE TOOLS》 (国际人工智能工具杂志)

年 卷 期：2014年第23卷第5期

页      面：1450006-1450006页

核心收录：

学科分类：08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

主　　题：Flexible job shop scheduling immune algorithm (IA) quantum evolutionary algorithm 

摘      要：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.