Metaheuristic Optimization Backgrounds: A Literature Review

摘要

Solving optimization problems becomes a central theme not only on operational research but also on several research areas like robotic, medicine, economic etc. The number of support decision problems that can be formalized as an optimization problem is growing rapidly. This study represents a literature revue of Metaheuristics optimization. Metaheuristics are applied to all kinds of combinatorial problems, and they can also be adapted to continuous problems. These approaches which include the simulated annealing method, genetic algorithms, taboo search method, the Ant Colony Algorithms, particle swarm optimization (PSO) etc. are for both mono-objective problems and multi-objective problems. The first area analyzes the inherent difficulties of each objective function, while the second treats the case of the simultaneous presence of several objectives. We will see that the tow aspects are often related in practice. Before focusing on the multi-objective optimization, it is necessary to explain the context of the mono-objective optimization. A special attention is given to the method of particle swarm optimization (PSO).