A genetic algorithm for job shop

Genetic algorithms (GAs) constitute a technique that has been applied with advantage to a variety of combinatorial problems. This work shows how the GAs can be used to optimize the job shop problem with many tasks, many machines, and precedence constraints. The authors introduce the technique of GAs and then show what makes the treatment of the job shop scheduling difficult. They then present an encoding of the problem that overcomes these difficulties. The performance of the algorithm is demonstrated with examples of real-world size.<
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