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Due-window assignment scheduling with variable job processing times.

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Area of Science:

  • Operations Research
  • Scheduling Theory
  • Production Management

Background:

  • Job scheduling problems often involve fixed processing times, but real-world scenarios include variable durations.
  • Learning and deteriorating effects significantly impact job processing times based on sequence or start time.
  • Due-window assignment is crucial for managing job earliness and tardiness costs.

Purpose of the Study:

  • To develop an efficient method for solving the single-machine scheduling problem with position-dependent or time-dependent processing times.
  • To simultaneously determine optimal due-windows and job processing sequences.
  • To minimize a comprehensive cost function encompassing earliness, tardiness, window parameters, and weighted tardy jobs.

Main Methods:

  • Formulation of a scheduling problem considering variable job processing times due to learning or deteriorating effects.
  • Development of an algorithm to determine optimal due-windows and processing sequences concurrently.
  • Analysis of the cost function including earliness, tardiness, window location, window size, and weighted tardy jobs.

Main Results:

  • The proposed scheduling problem with due-window assignment and variable processing times is proven to be solvable.
  • A polynomial-time algorithm exists for finding the optimal solution.
  • The method effectively minimizes the combined cost of earliness, tardiness, and other window-related factors.

Conclusions:

  • The simultaneous optimization of due-windows and job sequences is feasible and efficient.
  • The model provides a practical approach for scheduling problems with complex processing time variations.
  • This research contributes a polynomial-time solvable model for a common scheduling challenge.