Abstract
In multiobjective optimization, it is one of main issues how to obtain Pareto optimal solutions, and how to choose one solution from many Pareto optimal solutions. To this end, interactive optimization methods [47, 86, 126, 143, 153, 156], e.g., aspiration level method [96] introduced in Chap. 2, have been developed. Aspiration level method searches a final solution by processing the following two stages repeatedly (1) solving auxiliary optimization problem to obtain the closest Pareto optimal solution to a given aspiration level of decision maker and (2) revising her/his aspiration level by making the tradeoff analysis. Conventional interactive optimization methods are useful in particular in cases with many objective functions, in which it is difficult to visualize Pareto frontier, and also to depict the tradeoff among many objective functions.
Published Version
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