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- W31009406 abstract "This chapter considers job-shop scheduling problems, which determine a processing order of operations on each machine in order to minimize the maximum completion time. By incorporating the concept of similarity among individuals into the genetic algorithm that uses a set of completion times as individual representation and the Giffler and Thompson algorithm-based crossover, an efficient genetic algorithm for job-shop scheduling problems is presented. As illustrative numerical examples, 6 x 6, 10 x 10, and 15 x 15 job-shop scheduling problems are considered. The comparative numerical experiments with simulated annealing and the branch and bound method for job-shop scheduling problems are also demonstrated." @default.
- W31009406 created "2016-06-24" @default.
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- W31009406 date "2002-01-01" @default.
- W31009406 modified "2023-09-23" @default.
- W31009406 title "Genetic Algorithms for Job-Shop Scheduling" @default.
- W31009406 doi "https://doi.org/10.1007/978-1-4615-1519-7_9" @default.
- W31009406 hasPublicationYear "2002" @default.
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