Dynamic Multi-Objective Optimization Problems (DMOPs) and Many-Objective (MaOPs) are two classes of the optimization field that have potential applications in engineering. Modified Evolutionary Algorithms hybrid approaches seem to be suitable effectively deal with such problems. However, standard Crow Search Algorithm has not been considered for either DMOPs or MaOPs date. This paper proposes a...

In this paper, a new version of multi-objective differential evolution with dynamically adaptable mutation factor is used for Pareto optimization of a 5-degree of freedom vehicle vibration model excited by non-stationary random road profile. In this way, non-dominated sorting algorithm and crowding distance criterion have been combined to differential evolution with fuzzified mutation in order ...

We study a variant of the two-phase method for general bi-objective combinatorial optimization problems. First, we analyze a basic enumerative procedure, often used in literature to solve specific bi-objective combinatorial optimization problems, making it suitable to solve general problems. We show that the procedure generates the exact set E of efficient points by solving exactly 2|E| − 1 sin...

This paper presents a way to obtain parameters of a direct-axis equivalent circuit of a synchronous generator from frequency response data using bi-objective genetic algorithms. The genetic algorithms is capable of finding a global minimum within a given search interval. The sum square error of magnitude and phase of the d-axis equivalent circuit transfer function to formulate a bi-objective op...