In this book we introduce a new procedure called α-Discounting Method for Multi-Criteria Decision Making (α-D MCDM), which is as an alternative and extension of Saaty Analytical Hierarchy Process (AHP). It works for any number of preferences that can be transformed into a system of homogeneous linear equations. A degree of consistency (and implicitly a degree of inconsistency) of a decision-making problem are defined. α-D MCDM is afterwards generalized to a set of preferences that can be transformed into a system of linear and or non-linear homogeneous and or non-homogeneous equations and or inequalities. The general idea of α-D MCDM is to assign non-null positive parameters α_1, α_2, and so on α_p to the coefficients in the right-hand side of each preference that diminish or increase them in order to transform the above linear homogeneous system of equations which has only the null-solution, into a system having a particular non-null solution. After finding the general solution of this system, the principles used to assign particular values to all parameters αis the second important part of α-D, yet to be deeper investigated in the future. In the current book we propose the Fairness Principle, i.e. each coefficient should be discounted with the same percentage (we think this is fair: not making any favoritism or unfairness to any coefficient), but the reader can propose other principles. For consistent decision-making problems with pairwise comparisons, α-Discounting Method together with the Fairness Principle give the same result as AHP. But for weak inconsistent decision-making problem, α-Discounting together with the Fairness Principle give a different result from AHP. Many consistent, weak inconsistent, and strong inconsistent examples are given in this book.
CSIR-Structural Engineering Research Centre（印度科学与工业研究委员会-结构工程研究中心）；Academy of Scientific and Innovative Research（科学与创新研究院）
In multi-criteria decision making (MCDM) problems, ratings are assigned to the alternatives on different criteria by the expert group. In this paper, we propose a thermodynamically consistent model for MCDM using the analogies for thermodynamical indicators - energy, exergy and entropy. The most commonly used method for analysing MCDM problem is Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). The conventional TOPSIS method uses a measure similar to that of energy for the ranking of alternatives. We demonstrate that the ranking of the alternatives is more meaningful …
The process of multiple criteria decision making (MCDM) is of determining the best choice among all of the probable alternatives. The problem of supplier selection on which decision maker has usually vague and imprecise knowledge is a typical example of multi criteria group decision-making problem. The conventional crisp techniques has not much effective for solving MCDM problems because of imprecise or fuzziness nature of the linguistic assessments. To find the exact values for MCDM problems is both difficult and impossible in more cases in real world. So, it is more reasonable to consider th…
We introduce a method for explaining the results of various linear and hierarchical multi-criteria decision-making (MCDM) techniques such as WSM and AHP. The two key ideas are (A) to maintain a fine-grained representation of the values manipulated by these techniques and (B) to derive explanations from these representations through merging, filtering, and aggregating operations. An explanation in our model presents a high-level comparison of two alternatives in an MCDM problem, presumably an optimal and a non-optimal one, illuminating why one alternative was preferred over the other one. We sh…
Unveiling and unraveling aggregation and dispersion fallacies in group MCDM
Vrije Universiteit Amsterdam（阿姆斯特丹自由大学）；Jheronimus Academy of Data Science（耶罗尼米斯数据科学学院）；Eindhoven University of Technology（埃因霍温理工大学）；Delft University of Technology（代尔夫特理工大学）
Southwest Petroleum University（西南石油大学）；Zhuhai College of Jilin University（吉林大学珠海学院）；Karadeniz Technical University（黑海技术大学）；Shandong University of Finance and Economics（山东财经大学）；Shandong University（山东大学）；Beijing University of Technology（北京工业大学）
The picture fuzzy set, characterized by three membership degrees, is a helpful tool for multi-criteria decision making (MCDM). This paper investigates the structure of the closed operational laws in the picture fuzzy numbers (PFNs) and proposes efficient picture fuzzy MCDM methods. We first introduce an admissible order for PFNs and prove that all PFNs form a complete lattice under this order. Then, we give some specific examples to show the non-closeness of some existing picture fuzzy aggregation operators. To ensure the closeness of the operational laws in PFNs, we construct a new class of p…
Combined Compromise for Ideal Solution (CoCoFISo): a multi-criteria decision-making based on the CoCoSo method algorithm
Institut de Recherche en Informatique de Toulouse, IRIT（图卢兹信息学研究所）；Université Toulouse Capitole（图卢兹第一大学）；Université de Toamasina（图阿马西纳大学）；Universidad Internacional de Valencia（瓦伦西亚国际大学）；Universitat Politècnica de València（瓦伦西亚理工大学）
School of Information Technology and Electrical Engineering（信息技术与电气工程学院）；University of Queensland（昆士兰大学）
In reinforcement learning (RL), the goal is to obtain an optimal policy, for which the optimality criterion is fundamentally important. Two major optimality criteria are average and discounted rewards. While the latter is more popular, it is problematic to apply in environments without an inherent notion of discounting. This motivates us to revisit a) the progression of optimality criteria in dynamic programming, b) justification for and complication of an artificial discount factor, and c) benefits of directly maximizing the average reward criterion, which is discounting-free. Our contributio…
Supplier selection is a typical multi-criteria decision making (MCDM) problem and lots of uncertain information exist inevitably. To address this issue, a new method was proposed based on interval data fusion. Our method follows the original way to generate classical basic probability assignment(BPA) determined by the distance among the evidences. However, the weights of criteria are kept as interval numbers to generate interval BPAs and do the fusion of interval BPAs. Finally, the order is ranked and the decision is made according to the obtained interval BPAs. In this paper, a numerical exam…
National Institute of Technology, Durgapur（杜尔加布尔国立理工学院）
In this paper, a novel multiple criteria decision making (MCDM) methodology is presented for assessing and prioritizing medical tourism destinations in uncertain environment. A systematic evaluation and assessment method is proposed by integrating rough number based AHP (Analytic Hierarchy Process) and rough number based MABAC (Multi-Attributive Border Approximation area Comparison). Rough number is used to aggregate individual judgments and preferences to deal with vagueness in decision making due to limited data. Rough AHP analyzes the relative importance of criteria based on their preferenc…
Municipal solid waste management (MSWM) is a challenging issue of urban development in developing countries. Each country having different socio-economic-environmental background, might not accept a particular disposal method as the optimal choice. Selection of suitable disposal method in MSWM, under vague and imprecise information can be considered as multi criteria decision making problem (MCDM). In the present paper, TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) methodology is extended based on credibility theory for evaluating the performances of MSW disposal meth…
China University of Petroleum (East China)（中国石油大学（华东））；Newcastle University（纽卡斯尔大学）；Chandigarh University（昌迪加尔大学）；CGC College of Engineering（CGC工程学院）
With the development of science and technology and the need for Multi-Criteria Decision-Making (MCDM), the optimization problem to be solved becomes extremely complex. The theoretically accurate and optimal solutions are often difficult to obtain. Therefore, meta-heuristic algorithms based on multi-point search have received extensive attention. Aiming at these problems, the design strategy of hybrid flower pollination algorithm for Virtual Network Embedding (VNE) problem is discussed. Combining the advantages of the Genetic Algorithm (GA) and FPA, the algorithm is optimized for the characteri…
Evidence-Driven Decision Support for AI Model Selection in Research Software Engineering
organization= Department of Computer Science；Engineering, Shiraz University , city= Shiraz , country= Iran；organization= Wageningen University \& Research , city= Wageningen , country= The Netherlands
