Autors: Mateev, V. M., Marinova, I. Y.
Title: Modified chromosome pooling genetic algorithm for resource allocation optimization
Keywords: volutionary computation, Optimization problems, Chromosomes

Abstract: This paper presents an improved Genetic algorithm (GA) approach for resource allocation optimization. Modified chromosome pooling sub-stage for GA is proposed and tested on general algorithm performance. This sub-stage increases the combinatorial efficiency during GA chromosomes crossover and mutation. Modified chromosome pooling sub-stage for GA is suitable for structured topological optimization problems, with high order graphs. GA with modified chromosome pooling sub-stage is tested over the IEEE 13 Node Test Feeder, used as a benchmark problem for optimal power source distribution and control. Further development of this optimization GA approach can propose an efficient solution to other resource allocation optimization problems. The results obtained show the effectiveness of the proposed optimization model and influence of the combinatorial groups size and interconnection on general GA optimization performance.



    APPLICATIONS OF MATHEMATICS IN ENGINEERING AND ECONOMICS (AMEE’22): Proceedings of the 48th International Conference “Applications of Mathematics in Engineering and Economics”, vol. 2939, issue 1, 2023, Bulgaria, AIP Publishing, DOI 10.1063/5.0178510

    Copyright AIP Publishing

    Вид: публикация в международен форум, публикация в реферирано издание, индексирана в Scopus