Swarm intelligent algorithm for re-entrant hybrid flow shop scheduling problems. (2019)

• Record Type: Journal Article
• Authors: Han, Zhonghua; Tian, Xutian; Dong, Xiaoting; Xie, Fanyi
• Is Part Of: International journal of simulation and process modelling. Volume 14:Number 1(2019)
• Page Start: 17
• Page End: 27
• Publication Date: 2019
• Subjects: re-entrant hybrid flow shop -- RHFS -- mathematics scheduling models -- Hamming distance -- Levy flight -- swarm intelligent algorithm; Management -- Computer simulation -- Periodicals; Mathematical models -- Periodicals; Operations research -- Periodicals; Simulation methods -- Periodicals; 003.05
• Languages: English
• ISSNs: 1740-2123

Abstract

In order to solve re-entrant hybrid flowshop (RHFS) scheduling problems and establish simulations and processing models, this paper uses wolf pack algorithm (WPA) as global optimisation. For local assignment, it takes minimum remaining time rule. Scouting behaviours of wolf are changed in former optimisation by means of Levy flight, extending searching ranges and increasing rapidity of convergence. When it comes to local extremum of WPA, dynamic regenerating individuals with high similarity adds diversity. Hamming distance is used to judge individual similarity for increased quality of individuals, enhanced search performance of the algorithm in solution space and promoted evolutionary vitality. A painting workshop in a bus manufacture enterprise owns typical features of re-entrant hybrid flowshop. Regarding it as the algorithm applied target, this paper focuses on resolving this problem with dynamic wolf pack algorithm based on levy flight (LDWPA). Results show that LDWPA can solve re-entrant hybrid flowshop scheduling problems effectively.