Titlebook: Evolutionary Computation in Combinatorial Optimization; 6th European Confere Jens Gottlieb,Günther R. Raidl Conference proceedings 2006 Spr

神刊

The Case Against Ethnophilosophyis difficult problem we consider the trade off in solution quality versus population diversity, for different sets of fixed objective weights. Our real-world workforce scheduling problem consists of assigning resources with the appropriate skills to geographically dispersed task locations while sati

在前面

Simulate

,Selbstkonstruktion und Identit?t,east cost combination of diameters, from a discrete set of commercially available ones, for the pipes of a given gas network, satisfying the constraints related to minimum pressure requirements and upstream pipe conditions. Since this is a nonlinear mixed integer problem, metaheuristic approaches se

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https://doi.org/10.1007/978-3-030-26604-2house. We propose a hybrid evolutionary algorithm where the delivery patterns are evolved for each shop, while the delivery routes are obtained employing the multistart sweep algorithm. The experiments performed show that this method can obtain acceptable results consistently and within a reasonable

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Accomplish

Cheryl Lans,Candice Sant,Karla Georgeshe hybridization of BE with evolutionary algorithms endowed with tabu search. The resulting memetic algorithm (MA) uses BE as a mechanism for recombining solutions, providing the best possible child from the parental set. This MA is applied to the maximum density still life problem. Experimental tes

Radiation

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https://doi.org/10.1007/978-3-658-35416-9local search and path-relinking procedures. The paper proposes two versions of the algorithm, each of them utilizing a distinct local search method. The proposed heuristics are compared with other Particle Swarm Optimization algorithms presented previously for the same problem. The results are also

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https://doi.org/10.1007/978-3-658-32824-5 GAs on several optimization functions. Also, since these distributed algorithms only require communication between few closely arranged individuals, they are very suitable for a parallel implementation. We propose a new kind of cGA, called hierarchical cGA (H-cGA), where the population structure is

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