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Scheduling to minimize product design time using a genetic algorithm

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  • F. S. C. Lam

Abstract

We consider a scheduling problem encountered in a semiconductor manufacturing company where the time for designing products (or makespan) needs to be minimized. The problem can be stated as follows: there are sets of tasks (or jobs) to be performed in a design project by a set of engineers. Since engineers are qualified to perform a certain set of jobs, so they are considered to be nonidentical. However, a job can be worked on by more than one engineer while an engineer can work on one job at a time. Moreover, there is a precedence relation among the jobs. The problem is to schedule jobs to engineers so that the makespan is minimized. We develop a Genetic Algorithm (GA) for this problem, which is one of combinatorial optimization subjects to many practical constraints. The GA is found to be very effective for solving this intractable problem. This research attempts to study this scheduling problem in a scientific manner and to propose ways in which the task can be automated with the help of an algorithm embedded in a computer program.

Suggested Citation

  • F. S. C. Lam, 1999. "Scheduling to minimize product design time using a genetic algorithm," International Journal of Production Research, Taylor & Francis Journals, vol. 37(6), pages 1369-1386, April.
    • Handle: RePEc:taf:tprsxx:v:37:y:1999:i:6:p:1369-1386
    DOI: 10.1080/002075499191300
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    Cited by:

    1. Thomas Tong & C. M. Tam & Albert Chan, 2001. "Genetic algorithm optimization in building portfolio management," Construction Management and Economics, Taylor & Francis Journals, vol. 19(6), pages 601-609.

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