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A hybrid algorithm for task sequencing problems with iteration in product development

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  • Akposeiyifa J. Ebufegha
  • Simon Li

Abstract

Iteration is a major cause contributing to an increase in project duration and cost. By adopting the traditional models of design structure matrix and reward Markov chain, this paper proposes a hybrid algorithm for solving a task sequencing problem that aims for minimising the project duration. The proposed algorithm combines hierarchical clustering and genetic algorithms. This algorithmic strategy is intended to utilise the circuit concept to reduce the solution search space for GA. Our algorithm was compared to five other algorithms. Through numerical experiments, the proposed algorithm can solve large problems (number of tasks = 200), yield the same quality of solution results with shorter computational time, and deliver stable algorithmic performance.

Suggested Citation

  • Akposeiyifa J. Ebufegha & Simon Li, 2022. "A hybrid algorithm for task sequencing problems with iteration in product development," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 73(7), pages 1549-1561, July.
  • Handle: RePEc:taf:tjorxx:v:73:y:2022:i:7:p:1549-1561
    DOI: 10.1080/01605682.2021.1923376
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