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MIP-based heuristic algorithm for finite capacity MRP problem in hybrid flow shop with unrelated parallel machines

Author

Listed:
  • Watchara Songserm
  • Teeradej Wuttipornpun

Abstract

A main drawback of the material requirement planning (MRP) system is that it assumes fixed lead time, resulting in capacity problems recently called finite capacity material requirement planning (FCMRP). This paper proposes a mixed integer programming (MIP)-based heuristic algorithm that can solve the industrial scale FCMRP problem in hybrid flow shop with unrelated parallel machines. The heuristic is applied to construct an initial sequence of operations, whereas the MIP model is applied to determine the optimal machines and start times for the operations based on the initial sequence. The objective is to minimise the total cost, defined as the sum of tardiness, earliness, idle time, and work in process (WIP) holding costs. Performances of the proposed algorithm are evaluated using real data from automotive industries. The result shows that the total cost of the proposed algorithm are substantially reduced compared with the recent FCMRP algorithm (HGATS). Moreover, the required runtime is within a practical limit.

Suggested Citation

  • Watchara Songserm & Teeradej Wuttipornpun, 2019. "MIP-based heuristic algorithm for finite capacity MRP problem in hybrid flow shop with unrelated parallel machines," International Journal of Industrial and Systems Engineering, Inderscience Enterprises Ltd, vol. 33(2), pages 181-203.
    • Handle: RePEc:ids:ijisen:v:33:y:2019:i:2:p:181-203
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