FC-MOEO/AEP multi-objective optimization algorithm

Fast convergence multi-objective optimization algorithm appropriate for highly time-consuming objective functions.

In engineering, most problems require solving several objectives that usually conflict with each other. Evolutionary algorithms have emerged in recent years as an efficient approach to solving these complex optimization problems. These methods search for the optimal solutions by evaluating the objective functions multiple times. Evaluating objective functions is time consuming and sometimes costly in many engineering applications, such as structural optimal design problems. We introduce a new evolutionary algorithm called FC-MOEO /AEP, which has a high convergence speed and is suitable for solving such problems. In addition to its high convergence speed, this algorithm has intelligently balanced exploration and exploitation. This capability allows the algorithm to save itself easily from the local Pareto and estimate the global Pareto front with reasonable accuracy and dispersion.