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Parallel-batch scheduling and transportation coordination with waiting time constraint.

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This study tackles a complex parallel-batch scheduling problem involving raw material transport and waiting times. The research proves the problem

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Area of Science:

  • Operations Research
  • Industrial Engineering
  • Manufacturing Systems

Background:

  • Addresses parallel-batch scheduling with integrated raw material transportation and waiting time constraints.
  • Considers orders from various suppliers requiring transport to a manufacturing facility.
  • Each order must be processed within a limited waiting time after arrival.

Purpose of the Study:

  • To minimize the sum of total flow time and production cost in a parallel-batch scheduling system.
  • To analyze the computational complexity of the described scheduling problem.
  • To develop efficient algorithms for specific cases of the problem.

Main Methods:

  • Proving NP-hardness for the general and a special case (equal processing times).
  • Developing a pseudopolynomial-time dynamic programming algorithm.
  • Presenting a polynomial-time optimal algorithm for a specific scenario.

Main Results:

  • The general parallel-batch scheduling problem with transportation and waiting times is NP-hard in the strong sense.
  • The problem remains NP-hard even with equal processing times.
  • An optimal polynomial-time algorithm exists for the case of equal processing and transportation times.

Conclusions:

  • The studied scheduling problem is computationally complex, necessitating specialized algorithms.
  • Efficient solutions are achievable for specific, constrained versions of the problem.
  • The findings provide insights for optimizing manufacturing and logistics operations.