A PROMETHEE II-BELIEFapproach for multi-criteria decision-making problems with incomplete information

Multi-criteria decision aid methods consider decision problems in which many alternatives are evaluated on several criteria. These methods are used to deal with perfect information. However, in practice, it is obvious that this information requirement is too strict. In fact, the imperfect data provided by more or less reliable decision makers usually affect decision results, since any decision is closely linked to the quality and availability of information. In this paper, a PROMETHEE II-BELIEF approach is proposed to help multi-criteria decisions based on incomplete information. This approach solves problems with incomplete decision matrix and unknown weights within PROMETHEE II method. On the basis of belief function theory, our approach first determines the distributions of belief masses based on PROMETHEE II’s net flows, and then calculates weights. Subsequently, it aggregates the distribution masses associated with each criterion using Murphy’s modified combination rule in order to infer a global belief structure. The final alternative ranking is obtained via pignistic probability transformation. A case study of a real-world application concerning the location of a treatment center of waste from healthcare activities with infectious risk in the center of Tunisia is studied to illustrate the detailed process of the PROMETHEE II-BELIEF approach. Keywords: multiple criteria aid, incomplete information, PROMETHEE II method, belief function theory.

The multicriteria group decision making FlowSort method under uncertainty

Crisp values are insufficient to model real-life situations and imprecise ideas are frequently represented in multicriteria decision aid analysis. In fact, it is difficult to treat the evaluation criteria precisely and to fix exact preferences rating. The triangular intuitionistic fuzzy numbers succeeded to treat this kind of ambiguity in a great deal of research than other forms of fuzzy representation functions. The field of sorting issues is an active research topic in the multiple criteria decision aid (MCDA). This study extended one of the sorting methods, FLOWSORT, for solving multiple criteria group decision-making problems. This extension described the preferences rating of alternatives as linguistic terms which can be easily expressed in triangular intuitionistic fuzzy numbers. To validate our extension, an illustrative example as well as an empirical comparison with other multi-criteria decision making methods is presented. Keywords: multicriteria group decision making, sorting problematic, intuitionistic fuzzy set, FlowSort method

An extension of the codas method based on Interval Rough Numbers for multi-criteria group decision making

This study aims to develop a new Interval Rough COmbinative Distance-based Assessment (IR CODAS) method for handling multiple criteria group decision making problems using linguistic terms. A single decision maker is unable to express his opinions or preferences on multiple criteria decisions, while a Multi-Criteria Group Decision Making MCGDM process ensures successful outcomes when handling greater imprecision and vagueness information. A real-life case study of risk assessment is investigated using our proposed IR-CODAS method to test and validate its application; a sensitivity analysis is also performed. Keywords: Interval Rough Numbers, group decision making, IR-CODAS method, risk assessment.

A new multicriteria decision support tool based on Fuzzy SWARA and TOPSIS

The problem of selecting 3PL (Third Party Logistics) suppliers is a major issue in the management of the supply chain and the improvement of the production management of a manufacturing company. A 3PL supplier can be defined as a company that provides contract logistics services to a manufacturer, supplier or main user of a product or service. It is called a third party because the logistics provider does not own the products but participates in the supply chain between the manufacturer and the user of a given product. In actual cases, several decision-makers intervene in the selection of 3PL suppliers and each one has his own points of view and wishes to take into account criteria which are not generally the same for all the decision-makers. Furthermore, the criteria have different weights. In this study, we propose a method to solve this problem. It consists of a combination of the fuzzy Stepwise Weight Assessment Ratio Analysis (SWARA) method with the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). The objective is to optimize the decision-making process and have another, more dynamic model and satisfy the needs of the decision-maker. Fuzzy SWARA is one of the new methods being used for ranking evaluation criteria based on decision makers’ expected degree of importance to determine the weights of evaluation criteria (Selçuk, 2019). This method can be used to facilitate estimation of decision makers’ preferences regarding the meaning of attributes in the weight determination process. TOPSIS is a multi-criteria method for identifying solutions from a finite set of alternatives (Behzadian et al., 2012). To the best of our knowledge, this combination has not been developed in the literature, especially in the third-party logistic problems. The proposed model will be implemented to solve a 3PL problem of a company selling steel products. Keywords: multicriteria decision support, 3PL suppliers, Fuzzy SWARA, TOPSIS

MOLPTOL - a software package for sensitivityanalysis in MOLP

The paper introduces a new software package, MOLPTOL, for sensitivity analysis in multi-objective linear programming. In this application, which is available for free of charge on the web page (https:// sites.google.com/view/molptol), the tolerance approach as a measure of sensitivity is used. The motivation for creating MOLPTOL is the lack of such tools to date. MOLPTOL is novel for multi-criteria decision-making methods based on sensitivity analysis. The paper presents some new computational methods for obtaining the supremal tolerances as well. Keywords: multi-objective linear programming, sensitivity analysis, computer software.

A new application of the generalized traveling salesman problem in industry 4.0 and 5.0

A novel application of the generalized traveling salesman is pro- posed. The practical problem considered is optimization of different optimization criteria in various models of a mixed assembly worksta- tion. Several models that give rise to interesting optimization problems are discussed. Keywords: generalized traveling salesman problem, flexible assembly workstation.

Designing sustainable supply chains

A supply chain is a complex and dynamic supply and demand network of agents, activities, resources, technology and information involved in moving products or services from supplier to customer. The suitability of supply chains can be measured by multiple criteria, such as environmental, social, economic, and others. Finding an equilibrium between the interests of members of a sustainable supply chain is a very important problem. The main objective of the paper is to analyze the design of sustainable supply chains and to create a comprehensive model and solution methods for designing sustainable supply chains. Multiple criteria analysis and game theory is a natural choice to effectively analyze and model decision making in such multiple agent situation with multiple criteria where the outcome depends on the choice made by every agent. Multiple criteria analysis is useful for assessing sustainability of supply chains. The De Novo approach focusses on designing optimal systems. Game theory has become a useful instrument in the analysis of supply chains with multiple agents. Games are used for behavior modeling of supply chains; they focus on the allocation of resources, capacities, costs, revenues and profits. The co-opetition concept combines the advantages of both competition and cooperation into new dynamics, which can be used to not only generate more profits, but also to change the nature of the business environment for the benefit of users. Keywords: supply chain, sustainability, multiple criteria, De Novo approach, game theory, biform games.

A new approach for criteria weight elicitation of the ARAS-H method

Criteria weight inference is a crucial step for most of multi-criteria methods. However, criteria weights are often determined directly by the decision-maker (DM) which makes the results unreliable. Therefore, to overcome the imprecise weighting, we suggest the use of the preference programming technique. Instead of obtaining criteria weights directly from the DM, we infer them in a more objective manner to avoid the subjectivity and the unreliability of the results. Our aim is to elicit the ARAS-H criteria weights at each level of the hierarchy tree via mathematical programming, taking into account the DM’s preferences. To put it differently, starting from preference information provided by the DM, we proceed to model our constraints. The ARAS-H method is an extension of the classical ARAS method for the case of hierarchically structured criteria. We adopt a bottom-up approach in order to elicit ARAS-H criteria weights, that is, we start by determining the elementary criteria weights (i.e. the criteria at the lowest level of the hierarchy tree). The solution of the linear programs is obtained using LINGO software. The main contribution of our criteria weight elicitation procedure is in overcoming imprecise weighting without excluding the DM from the decision making process. Keywords: Multiple Criteria Decision Aiding, preference disaggregation, ARAS-H, criteria weights, mathematical programming.

An intuitionistic fuzzy extension of the CODAS-SORT method

Currently, an important issue in multi-criteria decision-making (MCDM) problems are vagueness and lack of precision of decision- -making information because of insufficient data and incapability of the decision maker to process the information. Intuitionistic fuzzy sets (IFS) are a solution to eliminate the vagueness and the uncertainty. While fuzzy sets (FS) deal with ambiguity and vagueness problem, IFSs have more advantages. Moreover, the CODAS-SORT method cannot handle the uncertainty and ambiguity of information provided by human judgments. The aim of this study is to develop an IF extension of CODAS-SORT combining this method with the IFS theory. To achieve this, we use the fuzzy weighted Euclidean distance and fuzzy weighted Hamming distance instead of the crisp distances. A case study of a supplier selection assessment is used to clarify the details of our proposed method. Keywords: multicriteria decision aid, sorting methods, CODAS-SORT, intuitionistic fuzzy set.

Wavelet decomposition approach for understanding time-varying relationship of financial sector variables: a study of the indian stock market

In this paper, we study the effect of overall stock market sentiment in India on sectoral indices and on individual stock prices in terms of co-movement, dependence and volatility transmission along with the magnitude and persistence of the effects. The study uses wavelet decomposition framework for breaking down different financial time series into time-varying components. Quantile Regression, Wavelet Multiple Correlation and Cross-Correlation analysis, and Diebold-Yilmaz spillover analysis are then applied to investigate the nature of dependence, association, and spillover dynamics. For further focus, we have considered different time periods separately to identify the effect of market phases. Interesting results are obtained with respect to persistence of shocks, both across and within time periods. These have implications with respect to understanding market behavior and also perception of sectors and stocks. Keywords: Wavelet Decomposition, SENSEX, Quantile Regression, Wavelet Multiple Correlation, Wavelet Multiple Cross Correlation, Diebold-Yilmaz Spillover.