General variable neighborhood search for the continuous optimization

Nenad Mladenovic, Milan Drazic, Kovacevic-Vujcic, Vera and Mirjana Cangalovic

European Journal of Operational Research, 2008, vol. 191, issue 3, pages 753-770

Abstract: We suggest a new heuristic for solving unconstrained continuous optimization problems. It is based on a generalized version of the variable neighborhood search metaheuristic. Different neighborhoods and distributions, induced from different metrics are ranked and used to get random points in the shaking step. We also propose VNS for solving constrained optimization problems. The constraints are handled using exterior point penalty functions within an algorithm that combines sequential and exact penalty transformations. The extensive computer analysis that includes the comparison with genetic algorithm and some other approaches on standard test functions are given. With our approach we obtain encouraging results.

Downloads: (external link)
http://www.sciencedi ... 0c22a09f3ec30f977147
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Access Statistics for this article

European Journal of Operational Research is edited by Roman Slowinski, Jesus Artalejo, Jean-Charles. Billaut, Robert Dyson and Lorenzo Peccati

More articles in European Journal of Operational Research from Elsevier
Series data maintained by Heidi Boesdal ().