Application of Genetic Algorithm on Job Shop Scheduling Problem to Minimise Makespan
International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
www.ijsr.net | Open Access | Fully Refereed | Peer Reviewed International Journal

ISSN: 2319-7064

Survey Paper | Computer Science & Engineering | India | Volume 5 Issue 6, June 2016

Application of Genetic Algorithm on Job Shop Scheduling Problem to Minimise Makespan

Anshulika, L. A. Bewoor

Scheduling of large number of jobs/tasks is a tedious and time taking work. With the increase is demand of products, the manufacturing industries have been facing a lot of trouble in fulfilling those demands while optimizing the production. Job shop scheduling problem (JSSP) is a well known combinatorial optimization problem with NP hard difficulty. Job shop scheduling (JSS) is the efficient allocation of shared resources (M) to competing jobs (J) such that a specific optimization criterion is satisfied. The complexity of JSS is (J!) ^M, which makes it NH hard. Various techniques have been used to solve the JSS problem till date. Metaheuristic techniques like Genetic Algorithm (GA) have shown good results and have been proven to be better performers than other techniques.

Keywords: Job shop scheduling JSS, Genetic Algorithm GA, metaheuristic, optimization

Edition: Volume 5 Issue 6, June 2016

Pages: 1726 - 1729

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How to Cite this Article?

Anshulika, L. A. Bewoor, "Application of Genetic Algorithm on Job Shop Scheduling Problem to Minimise Makespan", International Journal of Science and Research (IJSR), https://www.ijsr.net/search_index_results_paperid.php?id=NOV164660, Volume 5 Issue 6, June 2016, 1726 - 1729

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