Design and improvement of multi-level decision-making models

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Tezin Türü: Doktora

Tezin Yürütüldüğü Kurum: Orta Doğu Teknik Üniversitesi, Mühendislik Fakültesi, Elektrik ve Elektronik Mühendisliği Bölümü, Türkiye

Tezin Onay Tarihi: 2009

Öğrenci: ULAŞ BELDEK

Danışman: MEHMET KEMAL LEBLEBİCİOĞLU

Özet:

In multi-level decision making (DM) approaches, the final decision is reached by going through a finite number of DM levels. Usually, in each level, a raw decision is produced first and then a suitable decision fusion technique is employed to merge the lower level decisions with the raw decision in the construction of the final decision of the present level. The basic difficulty in these approaches is the determination of how the consecutive levels should interact with each other. In this thesis, two different multi-level DM models have been proposed. The main idea in the first model, “hierarchical DM” (HDM), is to transfer the decisions of previous hierarchical levels to an upper hierarchy with some reliability values. These decisions are then fused using a suitable decision fusion technique to attain more consistent decisions at an upper level. The second model “local DM in multiplelevels” (LDM-ML) depends on what may be called as local DM process. Instead of designing an agent to perform globally, designing relatively simple agents which are supposed to work in local regions is the essence of the second idea. Final decision is partially constructed by contribution of a sufficient number of local DM agents. A successful local agent is retained in the agent pool whereas a local agent not successful enough is eliminated and removed from the agent pool. These models have been applied on two case studies associated with fault detection in a four-tank system and prediction of lotto sales.