Group for Research in Decision Analysis


High Performing Evolutionary Techniques for Solving Complex Location Problems in Industrial System Design

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We propose an overall reconstruction of the traditional genetic algorithm method so that its inherent weaknesses such as slow convergence can be overcome. We explore a number of variations of crossover operators and of the genetic search scheme. The algorithm is also implemented as a partially parallel algorithm on a multi-processors workstation and is capable of handling a large class of real life location problems. Hub location problems from airline networks and location-allocation problems from the oil industry have been solved successfully.

, 21 pages