Multiprocessor task scheduling in multistage hybrid flow-shops: A parallel greedy algorithm approach

Cengiz Kahraman, Orhan Engin, Ihsan Kaya*, R. Elif Öztürk

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

99 Citations (Scopus)

Abstract

Hybrid flow shop scheduling problems have a special structure combining some elements of both the flow shop and the parallel machine scheduling problems. Multiprocessor task scheduling problem can be stated as finding a schedule for a general task graph to execute on a multiprocessor system so that the schedule length can be minimized. Hybrid Flow Shop Scheduling with Multiprocessor Task (HFSMT) problem is known to be NP-hard. In this study we present an effective parallel greedy algorithm to solve HFSMT problem. Parallel greedy algorithm (PGA) is applied by two phases iteratively, called destruction and construction. Four constructive heuristic methods are proposed to solve HFSMT problems. A preliminary test is performed to set the best values of control parameters, namely population size, subgroups number, and iteration number. The best values of control parameters and operators are determined by a full factorial experimental design using our PGA program. Computational results are compared with the earlier works of Oǧuz et al. [1,3], and Oǧuz [2]. The results indicate that the proposed parallel greedy algorithm approach is very effective in terms of reduced total completion time or makespan (C max) for the attempted problems.

Original languageEnglish
Pages (from-to)1293-1300
Number of pages8
JournalApplied Soft Computing
Volume10
Issue number4
DOIs
Publication statusPublished - Sept 2010

Keywords

  • Hybrid flow shop
  • Multiprocessor tasks scheduling problems
  • Parallel greedy algorithm

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