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Some single-machine scheduling problems with learning effects and two competing agents.

Hongjie Li1, Zeyuan Li2, Yunqiang Yin3

  • 1Mathematics Department, Zhoukou Normal University, Zhoukou 466001, China.

Thescientificworldjournal
|July 11, 2014
PubMed
Summary
This summary is machine-generated.

This study addresses job scheduling for two competing agents with time-dependent processing times. It explores optimizing schedules for objectives like maximum cost and weighted completion time.

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Area of Science:

  • Operations Research
  • Computer Science
  • Applied Mathematics

Background:

  • Considers a single-machine scheduling environment with two agents.
  • Jobs have processing times that are a decreasing linear function of their start times.
  • Agents compete for machine access with distinct optimization objectives.

Purpose of the Study:

  • To develop job assignment strategies that balance the objectives of two competing agents.
  • To analyze scheduling problems involving maximum cost, total weighted completion time, and discounted total weighted completion time.
  • To investigate the computational complexity and develop algorithms for these multi-agent scheduling problems.

Main Methods:

  • Formulation of three distinct scheduling problems based on agent objective combinations.
  • Analysis of computational complexity for each problem variant.
  • Development of solution algorithms for tractable problem instances.

Main Results:

  • Characterization of the complexity for different objective function pairings.
  • Presentation of algorithms for specific scheduling scenarios.
  • Insights into the trade-offs between competing agent objectives.

Conclusions:

  • The study provides a framework for analyzing and solving complex scheduling problems with competing agents.
  • Findings offer practical implications for resource allocation and scheduling in multi-user environments.
  • Highlights the importance of considering time-dependent processing times in scheduling optimization.