Industrial Engineering and Management Systems

  • 제10권4호
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  • Pages.247-254
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  • 2011
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  • 1598-7248(pISSN)
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  • 2234-6473(eISSN)
대한산업공학회 (Korean Institute of Industrial Engineers)
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Single-Machine Total Completion Time Scheduling with Position-Based Deterioration and Multiple Rate-Modifying Activities

  • Kim, Byung-Soo (Department of Systems Management and Engineering, Pukyong National University) ;
  • Joo, Cheol-Min (Department of Systems and Management Engineering, Dongseo University)
  • 투고 : 2011.03.23
  • 심사 : 2011.09.07
  • 발행 : 2011.12.01
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초록

In this paper, we study a single-machine scheduling problem with deteriorating processing time of jobs and multiple rate-modifying activities which reset deteriorated processing time to the original processing time. In this situation, the objective function is to minimize total completion time. First, we formulate an integer programming model. Since the model is difficult to solve as the size of real problem being very large, we design an improved genetic algorithm called adaptive genetic algorithm (AGA) with spontaneously adjusting crossover and mutation rate depending upon the status of current population. Finally, we conduct some computational experiments to evaluate the performance of AGA with the conventional GAs with various combinations of crossover and mutation rates.

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참고문헌

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피인용 문헌

  1. A Study on Single Machine Scheduling with a Rate-Modifying Activity and Time-Dependent Deterioration After the Activity vol.30, pp.1, 2013, https://doi.org/10.7737/KMSR.2013.30.1.015
  2. An Improved Genetic Algorithm for Single-Machine Inverse Scheduling Problem vol.2014, pp.1563-5147, 2014, https://doi.org/10.1155/2014/370560
  3. Machine scheduling of time-dependent deteriorating jobs with determining the optimal number of rate modifying activities and the position of the activities vol.9, pp.1, 2015, https://doi.org/10.1299/jamdsm.2015jamdsm0007
  4. 단일 복구조정활동 하에 단계적 퇴화를 가지는 단일기계 생산일정계획 vol.37, pp.3, 2014, https://doi.org/10.11627/jkise.2014.37.3.43
  5. Optimisation of the reverse scheduling problem by a modified genetic algorithm vol.53, pp.23, 2011, https://doi.org/10.1080/00207543.2014.988890