Article ID: | iaor19961047 |
Country: | United Kingdom |
Volume: | 46 |
Issue: | 8 |
Start Page Number: | 958 |
End Page Number: | 976 |
Publication Date: | Aug 1995 |
Journal: | Journal of the Operational Research Society |
Authors: | Lai Young-Jou |
Keywords: | fuzzy sets, artificial intelligence: decision support |
An interactive multiple objective system technique (IMOST) is investigated to improve the flexibility and robustness of multiple objective decision making (MODM) methodologies. The interactive concept provides a learning process about the system, whereby the decision maker can learn to recognize good solutions, the relative importance of factors in the system, and then design a high-productivity and zero-buffer system instead of optimizing a given system. This interactive technique provides integration-oriented, adaptation and dynamic learning features by considering all possibilities of a specific domain of MODM problems which are integrated in logical order. It encompasses the decision-making processes of formulating problems, constructing a model, solving the model, testing/examining its solution, and improving/reshaping the model and its solution in a specific problem domain. Although IMOST deals with multiple objective programming problems, it also provides some valuable orientation of integrated system methodologies.