Continuous Variable Neighbourhood Search Algorithm Based on Evolutionary Metaheuristic Components: A Scalability Test

Variable neighbourhood search is a metaheuristic combining three components: generation, improvement, and shaking components. In this paper, we describe a continuous variable neighbourhood search algorithm based on three specialised evolutionary algorithms, which play the role of each aforementioned component: 1) an EA specialised in generating a good starting point as generation component, 2) an EA specialised in exploiting local information as improvement component, 3) and another EA specialised in providing local diversity as shaking component. We adopt the experimental framework proposed for the Special session on evolutionary algorithms and other metaheuristics for continuous optimization problems - a scalability test, for the ISDA´09 conference, to test the ability of the model of being scalable for high-dimensional problems.