Titlebook: Recent Advances in Evolutionary Computation for Combinatorial Optimization; Carlos Cotta,Jano Hemert Book 2008 Springer-Verlag Berlin Heid

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An Evolutionary Algorithm for the Solution of Two-Variable Word Equations in Partially Commutative Gn a subclass of these groups, transforming a problem in combinatorial group theory into one of combinatorial optimisation. We give results which indicate efficient and successful behaviour of the evolutionary algorithm, hinting at the presence of a new degenerate deterministic solution and a framewo

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Determining Whether a Problem Characteristic Affects Heuristic Performanceuristic. Specifically, it reports a study on the effect of the cost matrix standard deviation of symmetric Travelling Salesman Problem (TSP) instances on the performance of Ant Colony Optimisation (ACO) heuristics. Results demonstrate that for a given instance size, an increase in the standard devia

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Performance and Scalability of Genetic Algorithms on NK-Landscapesions. Previous works that have focused mostly on recombination have shown that simple genetic algorithms, and some improved ones, perform worse than random bit climbers and not better than random search on landscapes of increased epistasis. In our work, in addition to recombination, we also study th

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Engineering Stochastic Local Search Algorithms: A Case Study in Estimation-Based Local Search for thbilistic travelling salesman problem, a paradigmatic combinatorial stochastic optimization problem. In fact, we have followed a bottom-up algorithm engineering process that starts from basic algorithms (here, iterative improvement) and adds complexity step-by-step. An extensive experimental campaign

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A Hybrid Optimization Framework for Cutting and Packing Problemseen heuristic and exact methods. A metaheuristic engine works as a generator of reduced instances for the original optimization problem, which are formulated as mathematical programming models. These instances, in turn, are solved by an exact optimization technique (solver), and the performance meas

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A Hybrid Genetic Algorithm for the DNA Fragment Assembly Problems a problem solved in the early phases of the genome project and thus very important, since the other steps depend on its accuracy. This is an NP-hard combinatorial optimization problem which is growing in importance and complexity as more research centers become involved on sequencing new genomes.

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An Iterative Heuristic Algorithm for Tree Decompositionitions is an NP-hard problem and different algorithms have been proposed in the literature for generation of tree decompositions of small width. In this chapter we present a new iterated local search algorithm to find good upper bounds for treewidth of an undirected graph. The iterated local search

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