As the problems concerning number of information to be optimised is increasing, optimisation level getting higher, target more diversified, and algorithms are becoming complex; traditional such as particle swarm differential evolution far from being able deal with this situation effectively, multi-objective evolutionary algorithm (MOEA) was born. Multi-objective help users quickly obtain data t...

At depots with refined oil shortage, arranging a reasonable distribution scheme limited supply affects operation costs, demand satisfaction rate of gasoline stations (hereafter, ‘station satisfaction’), and overtime penalty. This study considers the problem shortages using multi-objective optimisation approach from perspective decision makers marketing companies. The modelling solving process i...

Evolutionary Computation niching methods, such as Fitness Sharing and Crowding, are aimed at simultaneously locating and maintaining multiple optima to increase search robustness, typically in multi-modal function optimization. Such methods have been shown to be useful for both single and multiple objective optimisation problems. Niching methods have been adapted in recent years for other optim...