A dynamic co-evolution compact genetic algorithm for E/T problem. Issue 28 (2015)

• Record Type: Journal Article
• Authors: Han, Zhonghua; Zhu, Yihang; Lin, Shuo
• Is Part Of: IFAC-PapersOnLine. Volume 48:Issue 28(2015)
• Page Start: 1439
• Page End: 1443
• Publication Date: 2015
• Subjects: probabilistic models -- dynamic co-evolution -- compact genetic algorithm -- flexible flow shop -- earliness tardiness (E/T); Automatic control -- Periodicals; 629.805
• DOI: 10.1016/j.ifacol.2015.12.335
• Languages: English
• ISSNs: 2405-8963

Abstract

Abstract: In this paper, a dynamic co-evolution compact genetic algorithm (DCCGA) is proposed for flexible flow shop scheduling problem (FFSP) to minimize the total earliness and tardiness (E/T) penalties. In this new algorithm, a dynamic co-evolution mechanism containing two probabilistic models and a best individual inheritance strategy are integrated into the compact genetic algorithm (CGA). For improving the stability of the evolutionary trend in the evolution processes, the diversity of evolution trend and the convergence speed. Lastly, the experimental results show that, DCCGA outperforms CGA by 11.74% on the problem we study.