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SOCO
2012
Springer

Variable mesh optimization for continuous optimization problems

7 years 2 months ago
Variable mesh optimization for continuous optimization problems
Abstract Population-based meta-heuristics are algorithms that can obtain very good results for complex continuous optimization problems in a reduced amount of time. These search algorithms use a population of solutions to maintain an acceptable diversity level during the process, thus their correct distribution is crucial for the search. This paper introduces a new population meta-heuristic called ‘‘variable mesh optimization’’ (VMO), in which the set of nodes (potential solutions) are distributed as a mesh. This mesh is variable, because it evolves to maintain a controlled diversity (avoiding solutions too close to each other) and to guide it to the best solutions (by a mechanism of resampling from current nodes to its best neighbour). This proposal is compared with basic population-based meta-heuristics using a benchmark of multimodal continuous functions, showing that VMO is a competitive algorithm.
Amilkar Puris, Rafael Bello, Daniel Molina, Franci
Added 25 Apr 2012
Updated 25 Apr 2012
Type Journal
Year 2012
Where SOCO
Authors Amilkar Puris, Rafael Bello, Daniel Molina, Francisco Herrera
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