In order to understand the role of crossover in differential evolution, theoretical analysis and comparative study of crossover in differential evolution are presented in this paper. Two new crossover methods, namely consecutive binomial crossover and non-consecutive exponential crossover, are designed. The probability distribution and expectation of crossover length for binomial and exponentia...

This paper proposes method for solving steel alloying problem using evolution algorithms SOMA and differential evolution. Both algorithms belong to the family of the evolution algorithms but the main ideas of these algorithms are different. In differential evolution new offspring is created during the evolution, the individuals are crossed and mutated, while in SOMA the individuals move in the ...

This paper presents a comprehensive comparison between the performance of state-of-the-art genetic algorithms NSGA-II, SPEA2 and IBEA and their differential evolution based variants DEMO, DEMO and DEMO. Experimental results on 16 numerical multiobjective test problems show that on the majority of problems, the algorithms based on differential evolution perform significantly better than the corr...

determining the optimal location of wells with the aid of an automated search algorithm is a significant and difficult step in the reservoir development process. it is a computationally intensive task due to the large number of simulation runs required. therefore,the key issue to such automatic optimization is development of algorithms that can find acceptable solutions with a minimum number of...

The population-based evolutionary algorithms have emerged as powerful mechanism for finding optimum solutions of complex optimization problems. A promising new evolutionary algorithm, differential evolution, has garnered significant attention in the engineering optimization research. Differential evolution has the advantage of incorporating a relatively simple and efficient form of mutation and...

Complex systems provide an opportunity to analyze the essence of phenomena by studying their intricate connections. The networks formed these connections, known as complex networks, embody underlying principles governing system’s behavior. While have been previously applied in field evolutionary computation, prior studies limited ability reach conclusive conclusions. Based on our investigations...