Title: Multi-criteria M-machine SDST flow shop scheduling using modified heuristic genetic algorithm

Authors: D. Satyanarayana; M. Pramiladevi

Addresses: School of Mechanical Engineering, Vignan’s University, Vadlamudi, Guntur Dist. – 522 213, India ' Mechanical Engineering Department, Andhra University College of Engineering, Visakhapatnam, Andhra Pradesh (State), India

Abstract: The multi-criteria flow shop scheduling problem with sequence dependent setup times (SDST) is one of the most difficult class of scheduling problems. Efficient supervision of heuristics with SDST is one of the significant features to enhance the performance of manufacturing system. In this work, we have formulated multi-criteria decision-making flow shop scheduling problem. It consists of weighted sum of total weighted squared tardiness, makespan, total weighted squared earliness and number of tardy jobs. It is a very effective decision-making for scheduling jobs in modern manufacturing environment. In the present work, three efficient special heuristics based hybrid genetic algorithms (i.e., SHGA1, SHGA2, and SHGA3) are proposed for multi-criteria SDST. Experiments are conducted on the benchmark problems (Taillard, 1993). The performance of three SHGAs are tested, analysed and compared with the help of a defined performance index, known as relative percentage deviation (RPD). The maximum size of the problem is limited to 100 jobs and ten machines. From the results and analysis, the performance of SHGA3 found to be the best.

Keywords: muticriteria decision making; MCDM; flow shop scheduling; heuristics; hybrid genetic algorithms; sequence dependent setup times; SDST; makespan; total weighted squared tardiness; total weighted squared earliness; tardy jobs.

DOI: 10.1504/IJISE.2016.075203

International Journal of Industrial and Systems Engineering, 2016 Vol.22 No.4, pp.409 - 422

Received: 14 Jan 2014
Accepted: 06 Jul 2014
Published online: 08 Mar 2016 *

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