Improved Genetic Algorithm for Flow Shop Scheduling Problem at PT. XYZ

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Abstract

Scheduling according to Takeshi Yamada was an allocation of limited resources in order to do compete activity which usually applied on the operational research field where one of the examples was machine scheduling. Machine scheduling is an activity consisting of job (represent the activity) and machines (represent the resource) where each machine can process only one activity at a time. the purpose of scheduling is to perform all of the process from beginning to end with the objective to minimize makespan time. PT. XYZ is a manufacturing company that produces component for steam turbine component products in power plants. Within a year the company obtained an average of 9-10 project orders for each type of product. Because of the large number of projects that must be done, the scheduling process is becoming one of critical process in order to achieve the fastest makespan time. One way to find the fastest makespan time is by rescheduling using the methods applied in flow shop scheduling. One algorithm that can be used is the genetic algorithm. Based on the results of the research, it was found that for the process of scheduling project "A" with six machines and five jobs is makepan time of 53 days.

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APA

Widyawati, & Waliadi, G. (2020). Improved Genetic Algorithm for Flow Shop Scheduling Problem at PT. XYZ. In Journal of Physics: Conference Series (Vol. 1477). Institute of Physics Publishing. https://doi.org/10.1088/1742-6596/1477/2/022020

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