Titlebook: Evolutionary Computation in Combinatorial Optimization; 11th European Confer Peter Merz,Jin-Kao Hao Conference proceedings 2011 Springer Be

吹牛者

GPU-Based Approaches for Multiobjective Local Search Algorithms. A Case Study: The Flowshop Schedulocess. This paper presents a new methodology to design and implement efficiently GPU-based multiobjective local search algorithms. The experimental results show that the approach is promising especially for large problem instances.

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Connectedness and Local Search for Bicriteria Knapsack Problems, of running time and number of optimal solutions found. The experimental results indicate that this simple local search algorithm is able to find a representative set of optimal solutions in most of the cases, and in much less time than exact approaches.

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Evolutionary Multiobjective Route Planning in Dynamic Multi-hop Ridesharing,oblem in the dynamic multi-hop ridesharing. The experiments indicate that the evolutionary approach is able to provide a good quality set of route plans and outperforms the generalized label correcting algorithm in term of runtime.

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https://doi.org/10.1007/978-94-017-7173-3tance between repeated random perturbations of parameters, forming a statistical indication of EA stability under parameter perturbation. We then analyse the model for the wider class of general EAs, meaning our model may serve as a framework for parameter optimisation and stability analysis.

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European Cosmopolitanism in Question To illustrate the effectiveness of our approach, we apply it to four test problems: OneMax, Trap, OneMix and Subset Sum. We then contrast the predictions made by the . to the actual performance measured using the number of fitness evaluations. The results suggest that the new measure can reliably indicate problem hardness for EAs.

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Daniel Le Métayer,Julien Le Claincheheir geometric interpretation from continuous to general metric spaces. As an initial illustrative example, we show how Radial Basis Function Networks (RBFNs) can be used successfully as surrogate models to optimise combinatorial problems defined on the Hamming space associated with binary strings.

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John Garrard,Vera Tolz,Ralph Whiten. Our experiments show that the proposed approach is able to find improving solutions compared with a classical iterated local search. Moreover, the tradeoff between the exploitation of neutrality and the exploration of new parts of the search space is deeply analyzed.