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Differential evolution is a simple algorithm for global optimization. Basically it consists of three operations: mutation, crossover and selection. Despite many research papers dealing with the first two, hardly any attention has been paid to the third one nor is there a place for this operation in the algorithm basic naming scheme. In the paper we show that employing different selection strategies...
Differential Evolution (DE) is based on both an evolutionary strategy and a parallel direct search method employing a population. DE is an effective optimization method available for solving global optimization problem over continuous space. DE has a few control parameters that have to be set by users. This paper describes a new DE using Down-hill Simplex Method. Then we consider average distance...
Traveling salesman problem (TSP) is one of the most difficult problems in the combinatorial optimization area. The goal of TSP is to find one path that can travel between all the nodes (instances) of the graph just once (Hamiltonian tour) in the smallest tour, that is, smallest Euclidian distance. In this context, many other meta-heuristics techniques based on evolutionary algorithms have been propose...
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