Authors: M.K. Marichelvam; T. Prabaharan; Xin-She Yang; M. Geetha
Addresses: Department of Mechanical Engineering, Kamaraj College of Engineering and Technology, Virudhunagar, Tamilnadu, 626 001, India ' Department of Mechanical Engineering, Mepco Schlenk Engineering College, Sivakasi, Tamilnadu, 626 005, India ' Mathematics and Scientific Computing, National Physical Laboratory, Teddington, London TW11 0LW, UK ' Department of Mathematics, Kamaraj College of Engineering and Technology, Virudhunagar, Tamilnadu, 626 001, India
Abstract: This paper investigates the multistage hybrid flow shop (HFS) scheduling problems using the new bat algorithm. A HFS is the generalisation of flowshop with multiple machines. HFS is one of the important scheduling problems that represent many industries like iron and steel, chemical, textile and ceramic industries. The HFS scheduling problems have been proved to be NP-hard. A recently developed bat meta-heuristic algorithm is proposed to solve the HFS problems. The proposed algorithm is validated with a well-chosen set of benchmark problems in the literature. Computational results indicate that the proposed bat algorithm is more efficient than the genetic algorithm and particle swarm optimisation.
Keywords: hybrid flow shop scheduling; HFS scheduling; NP-hard; bat algorithm; makespan; metaheuristics; genetic algorithms; particle swarm optimisation; PSO.
International Journal of Logistics Economics and Globalisation, 2013 Vol.5 No.1, pp.15 - 29
Received: 08 May 2021
Accepted: 12 May 2021
Published online: 07 Jun 2013 *