MATLAB Code of Seeker Evolutionary Algorithm (SEA), a novel algorithm for solving continuous optimization problem




In recent years, there has been a significant growth in the development and application of the evolutionary algorithms. The structure of most algorithms had been obtained based on a phenomenon in nature.

In this study, a new algorithm is introduced to solve the continuous optimization problems. This algorithm is based on a simple seeking logic. The SEA divides the seeking area and seekers into several sections in each step and allocates every seeking group to a specific region. The motion of seekers in the regions is based on a simple evolutionary trend but none of the seekers is permitted to enter other regions. In the next stage, the regions with the best value of the objective function are selected and divided into several smaller sections and the seeker groups will be allocated to them accordingly. These steps will be continued until the stop condition is met. In order to assess the performance of this algorithm, from the available samples in articles, the most visited algorithms have been employed. The gained results show the advantage of the Seeker Evolutionary Algorithm in comparison to these algorithms.


Intelligent optimization, Meta-heuristic algorithms, Global optimization, Seeker Evolutionary Algorithm (SEA), Continuous Optimization

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