Bi Level Multi Level Multiple Criteria Decision Making And Topsis Approachtheory Applications And Software A Literature Review 2005 2015
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BI-LEVEL, MULTI –LEVEL MULTIPLE CRITERIA DECISION MAKING AND TOPSIS APPROACHTHEORY, APPLICATIONS AND SOFTWARE: A LITERATURE REVIEW (2005-2015)
This paper presents a literature review on the theory, applications and software of Bi-level, Multi –Level Multiple Criteria Decision Making and TOPSIS (Technique for Order Preference by Similarity Ideal Solution) Approach.
Multiple Criteria Decision Making in Application Layer Networks
Diploma Thesis from the year 2008 in the subject Computer Science - Commercial Information Technology, grade: 1,3, University of Bayreuth (Lehrstuhl für Wirtschaftsinformatik (BWL VII)), language: English, abstract: This work is concerned with the conduct of Multiple Criteria Decision Making (MCDM) by intelligent software agents trading digital commodities in Application Layer Networks (ALN) such as grids or clouds. These agents consider trustworthiness in their course of negotiation and select offers with respect to product price and seller reputation. To automate the selection process, we seek an appropriate MCDM method that provides clear advice for an agent prior to negotiating. We compare eleven well-known MCDM methods and choose the TOPSIS approach of Hwang and Yoon since it produces comprehensible and plausible results with a justifiable amount of effort. We modify the method and present a draft named xTOPSIS that promises intertemporal performance analysis for further automatation. The resulting tool is finally tested and evaluated in the context of a scenario similar to the eRep - Social Knowledge for e-Governance project.
Multi-Level Decision Making
This monograph presents new developments in multi-level decision-making theory, technique and method in both modeling and solution issues. It especially presents how a decision support system can support managers in reaching a solution to a multi-level decision problem in practice. This monograph combines decision theories, methods, algorithms and applications effectively. It discusses in detail the models and solution algorithms of each issue of bi-level and tri-level decision-making, such as multi-leaders, multi-followers, multi-objectives, rule-set-based, and fuzzy parameters. Potential readers include organizational managers and practicing professionals, who can use the methods and software provided to solve their real decision problems; PhD students and researchers in the areas of bi-level and multi-level decision-making and decision support systems; students at an advanced undergraduate, master’s level in information systems, business administration, or the application of computer science.