An effective co-evolutionary quantum genetic algorithm for the no-wait flow shop scheduling problem

• Published in: Advances in mechanical engineering Vol. 7; no. 12; p. 1
• Main Authors: Deng, Guanlong, Wei, Ming, Su, Qingtang, Zhao, Mei
• Format: Journal Article
• Language: English
• Published: London, England SAGE Publications 01.12.2015; Sage Publications Ltd; SAGE Publishing
• Subjects: Algorithms; Coding; Computer simulation; Evolutionary; Exploitation; Genetic algorithms; Mechanical engineering; Scheduling; scheduling; no-wait flow shop; competitive co-evolution; Genetic algorithm; evolutionary algorithm
• ISSN: 1687-8132; 1687-8140; 1687-8140
• DOI: 10.1177/1687814015622900

This article proposes a competitive co-evolutionary quantum genetic algorithm for the no-wait flow shop scheduling problem with the criterion to minimize makespan, which is a renowned NP-hard combinatorial optimization problem. An innovative coding and decoding mechanism is proposed. The mechanism uses square matrix to represent the quantum individual and adapts the quantum rotation gate to update the quantum individual. In the algorithm framework, the store-with-diversity is proposed to maintain the diversity of the population. Moreover, a competitive co-evolution strategy is introduced to enhance the evolutionary pressure and accelerate the convergence. The store-with-diversity and competitive co-evolution are designed to keep a balance between exploration and exploitation. Simulations based on a benchmark set and comparisons with several existing algorithms demonstrate the effectiveness and robustness of the proposed algorithm.