Hybrid Metaheuristic for Optimization Job-Shop Scheduling Problem

Home Page
About
Submit A Journal
Submit A Conference
Submit Paper/Book
- Submit a Preprint
- Submit a Book
Contact

International Journal of Informatics and Applied Mathematics
Volume:1 Issue:1
Hybrid Metaheuristic for Optimization Job-Shop Scheduling Problem

Hybrid Metaheuristic for Optimization Job-Shop Scheduling Problem

Authors : Benhamza KARİMA, Zedadra OUARDA

Pages : 1-9

View : 12 | Download : 7

Publication Date : 2018-12-20

Article Type : Research Paper

Abstract :Real Job-shop scheduling problem is one of the most difficult NP-Combinatorial issues. Exact resolution methods cannot handle large size cases. It is therefore necessary to use heuristic methods to solve them within a reasonable time. There are a large number of metaheuristic, which have the advantage of covering only part of the search space to find an acceptable solution. In this work, Genetic Algorithm and Simulated Annealing are used to solve Job-shop scheduling problem. The objective is to find the sequence of operations on the machines that will minimize the total time required to complete the set of jobs, also known as the `Makespan`. Compared to traditional genetic algorithm, hybrid approach yields significant improvement in solution quality.
Keywords : Scheduling Problem, Hybrid Metaheuristic, Optimization

ORIGINAL ARTICLE URL

VIEW PAPER (PDF)

* There may have been changes in the journal, article,conference, book, preprint etc. informations. Therefore, it would be appropriate to follow the information on the official page of the source. The information here is shared for informational purposes. IAD is not responsible for incorrect or missing information.