Adapt-MEMPSODE: a memetic algorithm with adaptive selection of local searches

MEMPSODE global optimization software tool integrates Particle Swarm Optimization, a prominent population–based stochastic algorithm, with well established efficient local search procedures. In the original description of the algorithm [17] a single local search with specific parameters was applied at selected best position vectors. In this work we present an adaptive variant of MEMPSODE where the local search is selected from a predefined pool of different algorithms. The choice of each local search is based on a probabilistic strategy that uses a simple metric to score the efficiency of the local search. This new version of the algorithm, Adapt-MEMPSODE, is benchmarked against BBOB 2013 test bed. The results show great improvement with respect to the static version that was also benchmarked in earlier work-shop