Titlebook: Evolutionary Computation in Combinatorial Optimization; 5th European Confere Günther R. Raidl,Jens Gottlieb Conference proceedings 2005 Spr

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Brendan Brown,Philippe Simonnota foundry. Three variants of genetic algorithm are considered, each of them using special crossover and mutation operators as well as repair functions. The real size test problems, based on the data taken from the production control system, are presented for assessment of the proposed algorithms. Th

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The Bulgarian Rejoinder to Youth Guaranteeor two variants of the Lin-Kernighan algorithm. Then we analyse the instances in those sets to guide us towards deferring general knowledge about the efficiency of the two variants in relation to structural properties of the symmetric travelling salesman problem.

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Centralizing Banking Resolution,strategies employ heuristics that exploit information about the partial colouring in an aim to improve performance. An evolutionary algorithm is used to drive the search. We compare the different strategies to each other on several very hard benchmarks and on generated problem instances, and show wh

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Ivan Illich and ,: A Reappraisaltisfying a set of hard-constraints and, as much as possible, some soft constraints. Here we work with a well-known version of the problem where there seems a strong case for considering these two goals as separate sub-problems. In particular we note that the satisfaction of hard constraints fits the

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András Kovács,Anikó Horváth,Zsuzsanna Vidra. employs heuristics in fitness definition, guiding the population to settle down in search areas where the individuals can not be improved by such heuristics. Some new theoretical improvements not present in early algorithms are now introduced. An application for pattern sequencing problems is exam

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Supporting Farmers or Consumers?mbines sequential estimation and combinatorial optimization methods to improve the execution time in dynamic optimization problems. It allows obtaining new high quality solutions in subsequent iterations using solutions found in previous time steps. The hybrid SSPF approach increases the performance