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
