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.
Birincil Dil | İngilizce |
---|---|
Konular | Yazılım Mühendisliği (Diğer) |
Bölüm | Makaleler |
Yazarlar | |
Yayımlanma Tarihi | 20 Aralık 2018 |
Kabul Tarihi | 13 Mart 2019 |
Yayımlandığı Sayı | Yıl 2018 Cilt: 1 Sayı: 1 |
International Journal of Informatics and Applied Mathematics