What is Multicriterion Decision Making?

Pomerol, Jean‐Charles; Barba-Romero, Sergio

doi:10.1007/978-1-4615-4459-3_1

Cited by 6 publications

(3 citation statements)

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“…It aims to find the most suitable solution according to the available data and criteria. 39 Figure 2 shows the multi-criteria decision-making process steps.…”

Section: Analytical Hierarchy Processmentioning

confidence: 99%

A new fast entropy‐based method to generate composite centrality measures in complex networks

Sabah

Şimşek

2023

Concurrency and Computation

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Summary Determining the centrality of nodes in complex networks provides practical benefits in many areas such as detecting influencer nodes, viral marketing, and preventing the spread of rumors. On the other hand, there is no consensus for the definition of centrality. Therefore, different centrality measures such as degree, closeness, and betweenness have been developed to measure the centrality of a node. However, each centrality measure highlights the various characteristics of the nodes in the network from its own point of view. This causes each centrality measure to rank the nodes in a different order. In recent years, researchers have focused on approaches that combine multiple centrality measures. Thus, the perspectives of different centrality measures can be considered simultaneously. In this study, we have proposed a fast and efficient method using the analytic hierarchy process and entropy weighting to combine multiple centrality measures. We tested the proposed method with synthetic and real datasets and compared the results with those of state‐of‐the‐art methods. The experimental results showed the proposed method to be competitive with these advanced methods, whereas it performed much better than the other methods in terms of computational speed. This indicated that our proposed method could be applied to large and dynamic complex networks.

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“…It aims to find the most suitable solution according to the available data and criteria. 39 Figure 2 shows the multi-criteria decision-making process steps.…”

Section: Analytical Hierarchy Processmentioning

confidence: 99%

A new fast entropy‐based method to generate composite centrality measures in complex networks

Sabah

Şimşek

2023

Concurrency and Computation

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“…Some of them are inserted in elaborated methodologies, and all of them use more or less complex mathematical procedures (for panoramas of such procedures, see e.g. Vincke [1992], Roy and Bouyssou [1993], Pomerol and Barba-Romero [2000], Belton and Stewart [2002], Ishizaka and Nemery [2013]).…”

Section: Theoretical Backgroundmentioning

confidence: 99%

Introduction

Bisdorff

Dias

Meyer

et al. 2015

Evaluation and Decision Models With Multiple Criteria

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This introductory chapter explains, first, the strategy guiding the editing of the MCDA application case studies. The second section illustrates the overall organization of the handbook into three parts: -a concise methodological introduction to the concepts of decision aiding, preference modelling and recommendation building; -the main part with fifteen case studies of MCDA applications; -and a short third part devoted to support tools for the MCDA process. The chapter ends with listing some highlights of the book content.

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“…The buyer defines strict β and preferences B with corresponding utilities u β (β i ) , as well as the threshold t β , and similarly the seller σ, S, u σ (σ j ) and t σ . Here we are not interested in how to compute t β ,t σ ,u β (β i ) and u σ (σ j ); we assume they are determined in advance by means of either direct assignment methods (Ordering, Simple Assessing or Ratio Comparison) or pairwise comparison methods (like AHP and Geometric Mean) [20]. Both agents inform the mediator about these specifications and the theory T they refer to.…”

Section: The Bargaining Processmentioning

confidence: 99%

Extending Propositional Logic with Concrete Domains for Multi-issue Bilateral Negotiation

Ragone

Noia

Sciascio

et al. 2008

Declarative Agent Languages and Technologies V

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We present a novel approach to knowledge-based automated one-shot multi-issue bilateral negotiation handling, in a homogeneous setting, both numerical features and non-numerical ones. The framework makes possible to formally represent typical situations in real e-marketplaces such as "if I spend more than 20000 e for a sedan then I want a navigator pack included" where both numerical (price) and non-numerical (sedan, navigator pack) issues coexist. To this aim we introduce P(N), a propositional logic extended with concrete domains, which allows to: model relations among issues (both numerical and not numerical ones) via logical entailment, differently from well-known approaches that describe issues as uncorrelated; represent buyer's request, seller's supply and their respective preferences as formulas endowed with a formal semantics. By modeling preferences as formulas it is hence possible to assign a utility value also to a bundle of issues, which is obviously more realistic than the trivial sum of utilities assigned to single elements in the bundle itself. We illustrate the theoretical framework, the logical language, the one-shot negotiation protocol we adopt, and show we are able to compute Pareto-efficient outcomes, using a mediator to solve a multi objective optimization problem.

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What is Multicriterion Decision Making?

Cited by 6 publications

References 0 publications

A new fast entropy‐based method to generate composite centrality measures in complex networks

A new fast entropy‐based method to generate composite centrality measures in complex networks

Introduction

Extending Propositional Logic with Concrete Domains for Multi-issue Bilateral Negotiation

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