An integrated decision aid system for Bosphorus water-crossing problem

Lee²,

Technological Forecasting and Social Change

2012

Abstract:Unstructured group decision-making is burdened with several central difficulties: unifying the knowledge of multiple experts in an unbiased manner and computational inefficiencies. In addition, a proper means of storing such unified knowledge for later use has not yet been established.Storage difficulties stem from of the integration of the logic underlying multiple experts' decisionmaking processes and the structured quantification of the impact of each opinion on the final product. To address these difficulties, this paper proposes a novel approach called the multiple agent-based knowledge integration mechanism (MAKIM), in which a fuzzy cognitive map (FCM) is used as a knowledge representation and storage vehicle. In this approach, we use particle swarm optimization (PSO) to adjust causal relationships and causality coefficients from the perspective of global optimization. Once an optimized FCM is constructed an agent based model (ABM) is applied to the inference of the FCM to solve real world problem. The final aggregate knowledge is stored in FCM form and is used to produce proper inference results for other target problems. To test the validity of our approach, we applied MAKIM to a real-world group decision-making problem, an IT project risk assessment, and found MAKIM to be statistically robust.

Section: Fuzzy Cognitive Mapsmentioning

confidence: 99%

Multi-agent knowledge integration mechanism using particle swarm optimization

Lee²,

Technological Forecasting and Social Change

2012

“…Its main advantages are that consists of a quite simple ranking method and follows a transparent computational procedure that is easy to understand by decision makers and stakeholders 9,39 . Due to these advantages, the method has attracted considerable attention in multiple fields such as supplier selection 14,38 , stock trading 3 , resources planing 1,13 or bankruptcy prediction 25 .…”

Section: Introductionmentioning

confidence: 99%

Pure linguistic PROMETHEE I and II methods for heterogeneous MCGDM problems

Espinilla¹,

Halouani²,

Chabchoub³

2015

IJCIS

The PROMETHEE methods basic principle is focused on a pairwise comparison of alternatives for each criterion, selecting a preference function type that often requires parameters in order to obtain a preference value. When a MCGDM problem is defined in an heterogeneous context, an adequate and common approach is to unify the involved information in linguistic values. However, for each criterion, there is a difficulty to select the specific preference function and define its parameters because they are expressed by crisp values in the unit interval, when the information involved in the problem has been unified into linguistic values. In this paper, a methodology for modeling linguistic preference functions in order to facilitate the selecting of each linguistic preference function type and the definition of its parameters is proposed, providing a more realistic definition of the criteria. Therefore, a generic linguistic preference function is proposed whose inputs and outputs are linguistic values. According to the generic linguistic preference function, six basic preference function types are extended for linguistic values. To do so, a linguistic difference function between linguistic values is defined, being its output, the input of the linguistic preference function. Furthermore, the proposed methodology is integrated in linguistic PROMETHEE I and II for heterogeneous MCGDM problems to obtain partial rankings and a full ranking of alternatives. So, the methodology provides pure linguistic PROMETHEE I and II that offer interpretability and understandability. Finally, the feasibility and applicability of pure linguistic PROMETHEE I and II are illustrated in a case study for the selection of a green supplier.

“…It is well adapted to problems where a finite number of alternative actions are to be ranked considering several, sometimes conflicting criteria [14]. According to Ülengin et al [15], advantages of PROMETHEE can be summarized as: (i) PROMETHEE is a user friendly outranking method, (ii) it has been successfully applied to real life planning problems and (iii) PROMETHEE I and PROMETHEE II allow both partial and total ranking of the alternatives while still satisfying simplicity. In MTS literature, Dağdeviren [13] have integrated AHP and PROMETHEE techniques for the equipment selection problem.…”

Section: Introductionmentioning

confidence: 99%

A Multi-Criteria Decision Making Approach for Machine Tool Selection Problem in a Fuzzy Environment

Özgen¹,

Tuzkaya²,

Tuzkaya³

et al. 2011

IJCIS

Tools and machines have an important effect on the manufacturing operations' effectiveness and the selection process of appropriate tools and machines is a complex issue with the consideration of multiple criteria. Considering the complexity of the problem area and the difficulties in machine tools evaluation processes, the main purpose of this study is to present a novel and effective methodology for machine tool selection problem. The proposed methodology constituted for this aim combines the modified DELPHI method, AHP (Analytical Hierarchy Process) and PROMETHEE (Preference Ranking Organization METHod for Enrichment Evaluations) approaches with fuzzy sets theory to be able to reflect the vagueness related to judgment of the decision-maker(s). A real life application is realized for pressing machine selection problem of a fixing products manufacturer from Turkey, Istanbul. The results of the proposed approach are compared with the results of fuzzy AHP-fuzzy TOPSIS approach. Additionally, sensitivity analyses are realized to show the changes in the results with the change in the criteria weights.