Vector mutable smart bee algorithm for engineering optimisation

摘要

Optimising and controlling complex engineering systems is a phenomenon that attracts the interest of numerous scientists. Till now, a variety of intelligent optimising and controlling techniques such as neural networks, fuzzy logic, game theory, support vector machines and stochastic algorithms were proposed to facilitate the engineering systems controlling process. Recently, a new optimising method called mutable smart bee (MSB) algorithm was proposed for optimising complex multi-modal problems. It has been shown that the method is a fast, powerful and robust optimising method since it hires a finite number of smart investigating agents in the problem's solution space. Here, a new concept of this model is inspired for preparing MSB algorithm to be applied on a multi-objective problem. Besides, some well-known Pareto base optimising algorithms such as non-dominated sorting genetic algorithm (NSGA-II) and strength Pareto evolutionary algorithm (SPEA 2) are utilised to confirm the acceptable performance of proposed method.