A Multi-Population Exploration-only Exploitation-only Hybrid on CEC-2020 Single Objective Bound Constrained Problems

摘要

Many meta-heuristics attempt to “transition” a single algorithm from exploration to exploitation. Conversely, previous research has shown that it can be better for the two distinct tasks of exploration and exploitation to instead be performed by two distinct algorithms/mechanisms. This has led to the development of Exploration-only, Exploitation-only Hybrid search techniques. This paper presents a Multi-Population Exploration only Exploitation-only Hybrid in which exploitation occurs in one population while a global search strategy performs exploration in another population. Unlike a sequential hybrid, this hybridization allows the exploratory technique (in this case Unbiased Exploratory Search) to delay convergence (up to indefinitely) which allows the hybrid system to benefit from a large budget of function evaluations. The new hybrid is evaluated on the CEC2020 test suite in the special session and competition on single objective bound constrained numerical optimization.