Skip to Main Content
Applications of interactive multiobjective optimization to existing complex problems often give rise to difficulties. The first is the difficulty encountered in constructing objectives, due to the complexity of each objective. To solve this difficulty, the authors have proposed to apply the multiattribute utiflity theory for constructing each objective. The second is the difficulty in convincing others of the selection of the resulting scenarios. To overcome this difficulty, the authors have proposed a posteriori esfimation of the multiattribute utility function composed of objectives in the model based solely on the data acquired during the interactive preferred solution searching. An application of these new methods to the industry allocation problem, which has been chosen as a case study, has demonstrated their usefulness and effectiveness; the former proposal proved to be easily applicable, and the utility function obtained by the latter proposal helps greatly in comprehending a decisionmaker's preference structure.