Ant colony algorithms for a two-agent scheduling with sum-of processing times-based learning and deteriorating considerations

  • Authors:

  • Wen-Hsiang Wu;Shuenn-Ren Cheng;Chin-Chia Wu;Yunqiang Yin

  • Affiliations:

  • Department of Healthcare Management, Yuanpei University, Hsinchu, Taiwan;Graduate Institute of Business Administration, Cheng Shiu University, Kaohsiung County, Taiwan;Department of Statistics, Feng Chia University, Taichung, Taiwan;College of Mathematics and Information Sciences, East China Institute of Technology, Fuzhou, China 344000

  • Venue:
  • Journal of Intelligent Manufacturing
  • Year:
  • 2012

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Abstract

This paper addresses a two-agent single-machine scheduling problem with the co-existing sum-of-processing-times-based learning and deteriorating effects. In the proposed model, it is assumed that the actual processing time of a job of the first (second) agent is a decreasing function of the sum-of-processing-times-based learning (or increasing function of the sum-of-processing-times-based deteriorating effect) in a schedule. The aim of this paper is to find an optimal schedule to minimize the total weighted completion time of the jobs of the first agent with the restriction that no tardy job is allowed for the second agent. For the proposed model, we develop a branch-and-bound and some ant colony algorithms for an optimal and near-optimal solution, respectively. Besides, the extensive computational experiments are also proposed to test the performance of the algorithms.