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2011•Advanced materials researchOpen access

The Study of Job Shop Scheduling Based on Genetic Algorithm

Jun Xing Xiong, Jin Ping Zhao, Hai Ning Tu

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Abstract

Aiming at Job Shop Scheduling Problem with Minimal Makespan, This paper is designed to use genetic algorithm to solve the problem of job shop scheduling, and also achieves the algorithm by using the C#. Application shows that the genetic algorithm to solve job shop scheduling problem is efficient and has good application value.

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What this paper is about

Aiming at Job Shop Scheduling Problem with Minimal Makespan, This paper is designed to use genetic algorithm to solve the problem of job shop scheduling, and also achieves the algorithm by using the C#. Application shows that the genetic algorithm to solve job shop scheduling problem is efficient and has good application value.

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OpenAlex reports 1 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

Aiming at Job Shop Scheduling Problem with Minimal Makespan, This paper is designed to use genetic algorithm to solve the problem of job shop scheduling, and also achieves the algorithm by using the C#. Application shows that the genetic algorithm to solve job shop scheduling problem is efficient and has good application value.

Key concepts: Job shop scheduling, Flow shop scheduling, Rate-monotonic scheduling, Computer science, Dynamic priority scheduling, Fair-share scheduling, Mathematical optimization, Job shop

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