Site selection for food distribution using rough set approach and TOPSIS method

q-Rung Orthopair Probabilistic Hesitant Fuzzy Rough Aggregation Information and Their Application in Decision Making

The core contribution of this study is to develop a novel generalized idea of q-rung orthopair probabilistic hesitant fuzzy rough set (q-ROPHFRS) which is hybrid structure of the q-rung orthopair fuzzy set, probabilistic hesitant fuzzy set, and rough set. The q-ROPHFRS covers the positive and negative membership grades in the form of probabilistic hesitant fuzzy rough information to address the uncertainties in real-world decision-making problems. This paper proposes a list of novel q-rung orthopair probabilistic hesitant fuzzy rough averaging/geometric aggregation operators to handle the uncertainty effectively and reliably to aggregate the uncertain information under q-ROPHFRSs. Several interesting elementary properties have been investigated. Furthermore, a novel multi-attribute decision-making approach based on the proposed aggregation information is presented. Finally, a numerical application regarding selecting a medical oxygen supplier to the hospital is presented to illustrate the consistency of the developed decision-making technique. The comparison of the proposed technique with q-rung orthopair probabilistic hesitant fuzzy rough TOPSIS shows that the proposed multi-criteria decision-making methodology is reliable and effective in addressing the uncertainty in real-world decision-making problems.

Evaluation and ranking of insurance companies by combining TOPSIS and the interval fuzzy rough sets

Corporate and organizational performance assessment is an important activity for both the managers and other stakeholders, as it provides them with an asset to evaluate their own strengths and weaknesses in relation to the competition, as well as guidelines for selecting appropriate measures to address the existing problems. The issue of criteria selection has been overcome through the literature review and the issue of criteria weights is handled by applying group decision making procedure. The procedure itself consists of using predefined linguistic expressions that are modelled by triangular fuzzy numbers and the aggregation of decision makers' opinion based on the rules of rough sets algebra. The values of the decision matrix are determined by prognosis method and they are described by crisp values. The proposed algorithm is tested on the insurance companies that operate in the Republic of Serbia.

A Novel Multi-Criteria Decision-Making Model: Interval Rough SAW Method for Sustainable Supplier Selection

Sustainability in a supply chain is a demand on the one hand and a challenge on the other. It is necessary to balance between these dimensions in order to fulfill the purpose of the supply chain. Therefore, in the first phase—i.e., in procurement—it is necessary to take into account its sustainability. In this paper, a sustainable supplier was selected respecting all three aspects of sustainability. The evaluation was carried out on the basis of a total of 21 criteria arranged into two levels and three groups. A new Interval Rough SAW (simple additive weighting) method, which represents a contribution to the treatment of problems belonging to the multi-criteria decision-making (MCDM), was developed. The integration of interval rough numbers with the SAW method was completed. In addition, the full consistency method (FUCOM) was applied to determine the weights of the criteria. The integrated FUCOM-Interval Rough SAW model enables treatment of multi-criteria problems while reducing subjectivity to the lowest possible level and eliminating uncertainties and ambiguities. The results obtained were determined throughout a sensitivity analysis consisting of a change in the weight of the criteria and the influence of dynamic matrices on the change in ranks. In addition, Spearman’s rank correlation coefficient (SCC) was calculated to confirm the stability of the previously obtained results.

Fresh Snack Food Channel Evaluation Model for Integrating Customers’ Perception of Transaction Costs in Taiwan

The primary purpose of this study was to explore how food dealers develop methods that facilitate transaction efficiency and how they select the optimal food channels. This study establishes a model according to the impact of transaction cost factors on consumers’ decision-making regarding purchase of fresh snack foods. Using fresh snack foods in Taiwan as an example, this study employed a fuzzy analytic network process to solve decision-making problems with multiple criteria by comparing the interaction between each transaction cost factor to obtain the factor weightings as well as the weightings of the transaction costs at each decision stage. This study found that food safety assurance and providing sufficient nutrition information were the most essential topics; thus, the optimal choice for snack food producers is to develop retail outlets. This study construction process proposed is innovative and operational, and the results may provide a reference for snack food dealers or microfood enterprises to assist them in developing their food channels.