The Development And Application Of Evolutionary Computation-Based Layered Encoding Cascade Optimization Model

Thesis ini mempersembahkan satu model umum pengoptimuman berlapisan berdasarkan perkomputeran evolusi yang dapat menyelesaikan pelbagai masalah pengoptimuman berkaitan pelbagai keputusan, pelbagai resolusi, interaktif, hibrid dan pelbagai objektif telah dipersembahkan. Dalam model yang dicadangkan, tumpuan diberi kepada algoritma genetik (GA) dan pengoptimuman partikel (PSO) dalam mekanisma pencarian evolusi. In this thesis, the research on a generic evolutionary-based layered encoding cascade optimization (LECO) model that is able to solve different kinds of optimization problems on multi-decision, multi-resolution, interactive, hybridized and multi-objective is presented. In the proposed model, particular attention is given to genetic algorithm (GA) and particle swarm optimization (PSO) in the development of evolutionary-based search mechanism