MEEF: A Minimum-Elimination-Escape Function Method for Multimodal Optimization Problems

Abstract EN

Auxiliary function methods provide us effective and practical ideas to solve multimodal optimizationproblems.

However, improper parameter settings often cause troublesome effects which might lead to thefailure of finding global optimal solutions.

In this paper, a minimum-elimination-escape function method isproposed for multimodal optimization problems, aiming at avoiding the troublesome “Mexican hat” effect andreducing the influence of local optimal solutions.

In the proposed method, the minimum-elimination functionis constructed to decrease the number of local optimum first.

Then, a minimum-escape function is proposedbased on the minimum-elimination function, in which the current minimal solution will be converted to theunique global maximal solution of the minimum-escape function.

The minimum-escape function is insensitiveto its unique but easy to adopt parameter.

At last, an minimum-elimination-escape function method is designedbased on these two functions.

Experiments on 19 widely used benchmarks are made, in which influences ofthe parameter and different initial points are analyzed.

Comparisons with 11 existing methods indicate thatthe performance of the proposed algorithm is positive and effective.