Differential evolution (DE) is well known as a simple and efficient scheme for global optimization over continuous spaces. In this paper we present two new, improved variants of D...
Differential evolution (DE) has emerged as one of the fast, robust, and efficient global search heuristics of current interest. This paper describes an application of DE to the aut...
A new mutation concept is proposed to generalize local selection based Differential Evolution algorithm to work in general multimodal problems. Three variations of the proposed me...
In this paper, we proposed Fittest Individual Refinement (FIR), a crossover based local search method for Differential Evolution (DE). The FIR scheme accelerates DE by enhancing...
In this paper, we consider the scenario that a population-based algorithm is applied to a numerical optimization problem and a solution needs to be presented within a given time bu...