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Survey Paper | Computer Science Engineering | Volume 5 Issue 6, June 2016 | Pages: 1726 - 1729 | India
Application of Genetic Algorithm on Job Shop Scheduling Problem to Minimise Makespan
Abstract: 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
How to Cite?: Anshulika, L. A. Bewoor, "Application of Genetic Algorithm on Job Shop Scheduling Problem to Minimise Makespan", Volume 5 Issue 6, June 2016, International Journal of Science and Research (IJSR), Pages: 1726-1729, https://www.ijsr.net/getabstract.php?paperid=NOV164660, DOI: https://dx.doi.org/10.21275/NOV164660