Multiobjective Optimization Using Evolutionary Algorithms - A Comparative Case Study
PPSN V Proceedings of the 5th International Conference on Parallel Problem Solving from Nature
A new analysis of the lebmeasure algorithm for calculating hypervolume
EMO'05 Proceedings of the Third international conference on Evolutionary Multi-Criterion Optimization
A probabilistic heuristic for a computationally difficult set covering problem
Operations Research Letters
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Determining the optimal layout of an intermodal terminal network, more specifically the optimal locations of the terminals, is a complicated matter that requires adequate decision support tools. In this paper, a bi-objective model is developed, minimizing both the transportation cost for the users of the terminal network, as well as the location cost for the terminal operators. A problem-specific GRASP (greedy randomized adaptive search procedure) is developed to solve the bi-objective terminal location problem efficiently. The algorithm only has a single parameter, that determines the allowed calculation time and can be used to improve the quality of the Pareto set approximation.