Int. J. of Industrial and Systems Engineering   »   2014 Vol.16, No.1

 

 

Title: Performance evaluation of an improved hybrid genetic scatter search (IHGSS) algorithm for multistage hybrid flow shop scheduling problems with missing operations

 

Authors: M.K. Marichelvam; T. Prabaharan

 

Addresses:
Department of Mechanical Engineering, Kamaraj College of Engineering and Technology, Virudhunagar 626001, Tamilnadu, India
Department of Mechanical Engineering, Mepco Schlenk Engineering College, Sivakasi 626005, Tamilnadu, India

 

Abstract: Multistage hybrid flow shop scheduling problems are considered in this paper. Each stage consists of several identical machines. The jobs are to be processed on any one of the machines at each stage. In most of the scheduling research works it is assumed that all jobs are to be processed at all stages. But in real-life industries some of the jobs may not be processed at some stages. Hence hybrid flow shop scheduling problems with missing operations are considered in this paper with the objective of determining a schedule that minimises makespan. The hybrid flow shop scheduling problems are non-deterministic polynomial time hard (NP-hard) problems. We propose a hybrid meta-heuristic algorithm, namely improved hybrid genetic scatter search (IHGSS) algorithm, based on genetic algorithm and scatter search algorithms. A case study problem of a leading steel furniture manufacturing company in India is presented to illustrate the proposed algorithm. Computational experiments show that the proposed IHGSS algorithm outperforms other heuristic and meta-heuristic algorithms.

 

Keywords: hybrid flow shops; HFS; NP-hard; heuristics; metaheuristics; genetic algorithms; improved HGSS; hybrid genetic scatter search; IHGSS; makespan; performance evaluation; flow shop scheduling; missing operations; steel furniture manufacturing; India.

 

DOI: 10.1504/IJISE.2014.057946

 

Int. J. of Industrial and Systems Engineering, 2014 Vol.16, No.1, pp.120 - 141

 

Available online: 28 Oct 2013

 

 

Editors Full text accessAccess for SubscribersPurchase this articleComment on this article