We found a match
Your institution may have rights to this item. Sign in to continue.
- Title
MOEA/D-GLS: a multiobjective memetic algorithm using decomposition and guided local search.
- Authors
Alhindi, Ahmad; Alhindi, Abrar; Alhejali, Atif; Alsheddy, Abdullah; Tairan, Nasser; Alhakami, Hosam
- Abstract
This paper proposes an idea of using well studied and documented single-objective optimization methods in multiobjective evolutionary algorithms. It develops a hybrid algorithm which combines the multiobjective evolutionary algorithm based on decomposition (MOEA/D) with guided local search (GLS), called MOEA/D-GLS. It needs to optimize multiple single-objective subproblems in a collaborative way by defining neighborhood relationship among them. The neighborhood information and problem-specific knowledge are explicitly utilized during the search. The proposed GLS alternates among subproblems to help escape local Pareto optimal solutions. The experimental results have demonstrated that MOEA/D-GLS outperforms MOEA/D on multiobjective traveling salesman problems.
- Subjects
TRAVELING salesman problem; EVOLUTIONARY algorithms; ALGORITHMS
- Publication
Soft Computing - A Fusion of Foundations, Methodologies & Applications, 2019, Vol 23, Issue 19, p9605
- ISSN
1432-7643
- Publication type
Article
- DOI
10.1007/s00500-018-3524-z