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A new adaptive Differential Evolution algorithm called EWMA-DE is proposed. In original Differential Evolution algorithm three different control parameter values must be pre-specified by the user a priori; Population size, crossover constant and mutation scale factor. Choosing good parameters can be very difficult for the user, especially for the practitioners. In the proposed algorithm the mutation...
In this paper, the authors propose a new differential evolution (DE) technique called Re-labeling Differential Evolution for combinatorial optimization. DE was proposed in 1995 by Stone and Price. DE is one of the techniques of evolutionary computation (EC), and efficiently solves optimization problems using difference vectors between individuals in continuous space. DE can efficiently solve problems...
Differential evolution (DE) algorithm is a promising global optimization approach, but its control parameters are sensitive to some difficult problems, and they must be adjusted artificially for different problems some times, which is really a time consuming work. In this paper, we present a new version of DE with self-adaptive control parameters. We call the new version efficient improved differential...
Differential Evolution(DE) is a kind of simple but powerful evolutionary optimization algorithm with many successful applications. However, it has some weaknesses, especially the slow convergence speed because of weak local search ability in its stochastic search. To overcome the drawback, we first employ the orthogonal design method with quantization technique to generate the initial population,...
The most popular solution concepts in game theory, Nash and Pareto equilibrium, have some limitations when applied in real life. Nash equilibrium rarely assures maximal payoff and the Pareto equilibrium is a set of solutions that is often too hard to process. Our aim is to find an equilibrium concept that provides a small set of efficient solutions and is equitable for all players. The Lorenz dominance...
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