Volume 7, Issue 5, October 2014, Pages 827 - 852
A Self-Adaptive Heuristic Algorithm for Combinatorial Optimization Problems
Cigdem Alabas-Uslu, Berna Dengiz
Received 22 March 2013, Accepted 18 January 2014, Available Online 1 October 2014.
- https://doi.org/10.1080/18756891.2014.966992How to use a DOI?
- Metaheuristics, Combinatorial optimization, Parameter tuning, Adaptive parameter
- This paper introduces a new self-tuning mechanism to the local search heuristic for solving of combinatorial optimization problems. Parameter tuning of heuristics makes them difficult to apply, as parameter tuning itself is an optimization problem. For this purpose, a modified local search algorithm free from parameter tuning, called Self-Adaptive Local Search (SALS), is proposed for obtaining qualified solutions to combinatorial problems within reasonable amount of computer times. SALS is applied to several combinatorial optimization problems, namely, classical vehicle routing, permutation flow-shop scheduling, quadratic assignment, and topological design of networks. It is observed that self-adaptive structure of SALS provides implementation simplicity and flexibility to the considered combinatorial optimization problems. Detailed computational studies confirm the performance of SALS on the suit of test problems for each considered problem type especially in terms of solution quality.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - JOUR AU - Cigdem Alabas-Uslu AU - Berna Dengiz PY - 2014 DA - 2014/10/01 TI - A Self-Adaptive Heuristic Algorithm for Combinatorial Optimization Problems JO - International Journal of Computational Intelligence Systems SP - 827 EP - 852 VL - 7 IS - 5 SN - 1875-6883 UR - https://doi.org/10.1080/18756891.2014.966992 DO - https://doi.org/10.1080/18756891.2014.966992 ID - Alabas-Uslu2014 ER -