An Adaptive Memory Procedure for Continuous Optimization

In this paper we consider the problem of finding a global optimum of an unconstrained multimodal function within the framework of adaptive memory programming, focusing on an integration of the scatter search and tabu search methodologies. Computational comparisons are performed on a test-bed of 11 types of problems. For each type, four problems are considered, each one with dimension 50, 100, 200 and 500 respectively; thus totalling 44 instances. Our results show that the scatter tabu search procedure is competitive with the state-of-the-art methods in terms of the average optimality gap achieved.