A hybrid fruit fly optimisation algorithm to solve the flow shop scheduling problems with multi-objectives. (2017)

• Record Type: Journal Article
• Authors: Marichelvam, M.K.; Azhagurajan, A.; Geetha, M.
• Is Part Of: International journal of advanced intelligence paradigms. Volume 9:Number 2/3(2017)
• Page Start: 164
• Page End: 185
• Publication Date: 2017
• Subjects: flowshop scheduling -- NP-hard -- makespan -- earliness -- tardiness -- mean flow time -- metaheuristics -- fruit fly optimisation -- multi-objective optimisation -- metaheuristics; Artificial intelligence -- Periodicals; Machine theory -- Periodicals; Fuzzy logic -- Periodicals; 006.305
• Languages: English
• ISSNs: 1755-0386

Abstract

Scheduling is one of the most important decision making processes in production and operations management. Different scheduling environments are addressed by the researchers in the literature. In this paper, flow shop scheduling problems are studied. Many researchers tackled with single objective flow shop scheduling problems with makespan objective only. However, scheduling problems consist of many conflict objectives. Hence, in this paper an attempt is made to solve the multi-objective flow shop scheduling problems. The objective is to minimise the weighted sum of makespan, mean flow time, earliness and tardiness. The flow shop scheduling problems have been proved to be NP-hard. Hence, the problems cannot be solved by the exact algorithms. In this paper, a relatively new meta-heuristic algorithm called as hybrid fruit fly optimisation algorithm is proposed to solve the multi-objective flow shop scheduling problems. Two constructive heuristics and a dispatching rule are incorporated with the fruit fly optimisation algorithm and hence the solution quality is improved. The proposed algorithm is tested on random problem instances and the results are compared with many other meta-heuristic algorithms. The results show that the proposed algorithm is more effective and better than other meta-heuristic algorithms.