A hybrid discrete firefly algorithm to solve flow shop scheduling problems to minimise total flow time. (2016)

• Record Type: Journal Article
• Authors: Marichelvam, M.K.; Geetha, M.
• Is Part Of: International journal of bio-inspired computation. Volume 8:Number 5(2016)
• Page Start: 318
• Page End: 325
• Publication Date: 2016
• Subjects: flow shop scheduling -- total flow time -- heuristics -- metaheuristics -- hybrid discrete firefly algorithm -- HDFA; Biologically-inspired computing -- Periodicals; Computational biology -- Periodicals; 572.0285
• Languages: English
• ISSNs: 1758-0366

Abstract

In this paper, we consider m-machine flow shop scheduling problems (FSSPs). The objective is to schedule the available n jobs to minimise the total flow time. The flow shop scheduling problems have been proved to be strongly non-deterministic polynomial-time hard (NP-hard). Hence, exact methods cannot be used to solve even small size problems. Researchers addressed many heuristics and meta-heuristics to solve the problems. Firefly algorithm (FA) is one of the recently developed meta-heuristic algorithms. We propose a hybrid discrete firefly algorithm (HDFA) to solve the FSSPs to minimise the total flow time. To validate the performances of the HDFA, computational experiments are conducted on a number of randomly generated test problems with different parameters and the results proved the effectiveness of the proposed algorithm.