The reactive power planning and dispatch problems have been solved using Genetic algorithm (GA), Differential evolution (DE) and Particle Swarm Optimization (PSO) technique in order to have a comparative study on the performance of these algorithms. It has been found that Differential evolution performs best followed by the Particle swarm optimization. Both DE and PSO can perform well even with...

This paper presents a dynamic optimization approach based on the differential evolution (DE) strategy which is applied to the concurrent optimal design of a continuously variable transmission (CVT). The structure-control integration approach is used to state the concurrent optimal design as a dynamic optimization problem which is solved using the Constraint Handling Differential Evolution (CHDE...

In this paper, an application of an adaptive differential evolution (DE) algorithm for training higher order neural networks (HONNs), especially the Pi-Sigma Network (PSN) has been introduced. The proposed algorithm is a variant of DE/rand/2/bin and possesses two modifications to avoid the shortcomings of DE/rand/2/bin. The base vector for perturbation is the best vector out of the three random...

The use of cutting fluid in manufacturing industries has now become more problematic due to environmental pollution and health related problems of employees. Also the minimization of cutting fluid leads to the saving of lubricant cost and cleaning time of machine, tool and work-piece. The concept of minimum Quantity Lubrication (MQL) has come in to practice since a decade ago in order to overco...

Differential evolution, termed DE, is a novel and rapidly developed evolution computation in recent years. There are some advantages of DE, including simple structure, easy use and rapid convergence speed. Besides, DE can be also applied on the complex optimization problem. However, there are some issues, such as premature convergence and stagnation, remaining in DE algorithm. To overcome those...

This chapter presents the application of Differential Evolution (DE) Algorithm for the VLSI floorplanning problems. DE Algorithm has been successfully applied to VLSI sequence pair representation. The important advantages of DE are its simplicity, fast convergence, and easy for implementation. DE algorithm is a population based algorithm like GA using similar operators such as crossover, mutati...

in this context, a novel structure has been proposed for simple differential evolutionary (de) algorithm to solve optimal recloser placement. for this, an operator is added to de algorithm to adapt concept of the problem. other contribution of this work is formulating a novel objective function. the proposed objective function has been formulated to improve four reliability indices which consis...

This article is an extended abstract of a doctoral dissertation on chess evaluation function tuning with differential evolution (DE) algorithm. DE is adopted for efficient chess evaluation function tuning, extended with an opposition-based optimization and a new history mechanism. Experimental results show that the algorithm is efficient and can be applied to the chess evaluation function tunin...

1. Introduction Let P(x,y) denote the number of integers specified in the title. A number of estimates and asymptotic formulae for this function have been given (cf. [1] and the literature mentioned there). Recently DE BRUIJN ([2]) proved an asymptotic formula for log f(x,y) which holds uniformly for 2 < y < x. Part of the proof consisted of showing that P(x y) > C 71(y) + u\ where u = [(log x)...

In the present paper, dynamic identification problem of a FE structure with unknown parameters is solved by global search method. Response surface methodology is introduced in Differential Evolution algorithm to improve the performance of the algorithm. Differential evolution (DE) is an evolutionary algorithm where N different vectors collecting the parameters of the system are chosen randomly ...