Individual Regret Research Articles

Performance Evaluation of Surface Roughness in the Boring Operation of IS 2062 E250 Plate on CNC Machine Using Combined Entropy-Decision Tree-VIKOR Approach

In boring E250 B0 steel material, the selection of process parameters is one of the most challenging tasks to achieve. The boring literature lacks understanding and fails to reveal how to select the important boring parameters for utmost resource distribution to the most important parameters. This article proposes a novel method to analyse the importance of parameters in boring to produce utmost surface roughness using the entropy-decision tree-VIKOR approach as a multi-criteria decision-making solution to the choice of process materials for superior surface roughness. The choice parameters include speed, depth of cut, feed and nose radius. The entropy approach was instituted to attain the weight of the diverse parameters. The decision tree approach is deployed through the classification of the parameters as beneficial and non-beneficial and the expected values at each mode evaluated. The desirable weightage is then established and serves as the input to the VIKOR approach. This converts the desirable weightage into unit measures through the best/worst value and weightage evaluation. The individual regrets are then analyzed and the final ranking obtained. Results revealed that the depth of cut is the most important parameter, then nose radius (0.98), feed (0.307) and speed (0), respectively. Therefore, a plan to assign more measures to the depth of cut may be developed and the least resources may be assigned to speed. This detail may be helpful to prepare the annual budgets for the boring operation on the factory floor.

Transition management theory-based policy framework for analyzing environmentally responsible freight transport practices

The freight transport industry of developing nations are trying very hard to achieve environmental sustainability in their logistics business. Meanwhile, it is essential to identify the transformation path towards sustainable freight transport for every nation. This paper has presented a framework based on transition management (TM) theory to identify, classify, and measure the important environmentally responsible transport practices (ERTPs). This work utilizes a two-step methodology comprised of a grey clustering (GC) algorithm and a compromise ranking method, i.e., VIseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) for prioritization of ERTPs performance. The GC algorithm is used to classify the ERTPs based on their impact on selected transport processes. Initially, this study identifies thirty-five ERTPs and four transport performance clusters. The proposed framework is validated with the Indian freight transport industry. The GC algorithm classifies twenty-one and fourteen practices as a high priority and moderate priority, respectively. The VIKOR method is used to compute the group utility, individual regret, and possibility value of high priority ERTPs. The ERTPs such as developing efficient freight terminal, compliance with government transport emission law and practice, promoting the use of the green container, environmental certification of freight carriers, and using alternative fuels are found as poor performing practices in the Indian freight transport industry. The proposed decision model robustness is tested with the sensitivity analysis, and a final ranking of the high priority ERTPs is presented. The outcomes of this research help logistics practitioners and policymakers in managing the ERTPs of freight logistics systems and develop a roadmap for improving freight transport sustainability.

Group decision-making based on complex spherical fuzzy VIKOR approach

The main objective of this study is to set up the foundations of a new model, namely, complex spherical fuzzy (CSF) model that is highly proficient to express the two dimensional ambiguous information. The absence of neutral membership in complex Pythagorean fuzzy sets to express abstinence part of opinion and limitation of spherical fuzzy sets to capture the two dimensional data motivated us to build up the theory of complex spherical fuzzy sets. To establish the ground-breaking CSF model, we elaborate the essential and rudimentary concepts including score degree, accuracy degree and comparison rule. Further, we define the primary operations that serve as helping tools to found four new aggregation operators, namely, complex spherical fuzzy weighted average (CSFWA) operator, complex spherical fuzzy ordered weighted average (CSFOWA) operator, complex spherical fuzzy weighted geometric (CSFWG) operator and complex spherical fuzzy ordered weighted geometric (CSFOWG) operator. These operators are of vital importance in aggregation of complex spherical fuzzy numbers (CSFNs). Moreover, we present a multi-skilled and high potential multi-criteria group decision-making (MCGDM) technique, namely, complex spherical fuzzy VIKOR (CSF-VIKOR) method using the grounds of VIKOR method and motivation of CSF model which is adequate to deal with two dimensional data. The working rule of the proposed technique emphasizes to propose a compromise solution depending upon two focal properties, namely, group utility and individual regret of opponent. We sort the alternatives via the ranking measure by the dint of ascending order. We accomplish the proposed MCGDM strategy by the means of a numerical example in the field of business to rank the objectives of an advertisement on Facebook. We validate the precision and veracity of the proposed strategy by comparing the results with spherical fuzzy VIKOR (SF-VIKOR) method. Finally, we analyze the proposed method to unfold its edge and dominance over the existing approaches.

Research on comprehensive evaluation of six “properties” for equipment products incorporating correlate indexes

The six “properties” for equipment products are critical indexes to improve the quality of equipment development and batch production. In view of current difficulties of auditing six “properties” and putting qualitative or quantitative evaluation into practices, this paper analyses interactive characteristics of six “properties” and organically integrates them based on the VIKOR method. Firstly, the indexes and connotation of six “properties” for equipment products have been elaborated. Secondly, specific relationship among six “properties” is analysed and their interactive coefficients are depicted as two additive fuzzy measures. Thirdly, the effect of interactive coefficient among six “properties” is analysed on group utility and individual regret in the VIKOR method, and specific decision-making steps based on the VIKOR method are also proposed. Finally, two illustrative cases show the differences of multiple indexes decision results under two kinds of conditions and the feasibility and effectiveness of the proposed methods.

Multi-criteria decision-making methods based on q-rung picture fuzzy information

The q-rung picture fuzzy sets serve the fuzzy set theory as a competent, broader and accomplished extension of q-rung orthopair fuzzy sets and picture fuzzy sets which exhibit excellent performance in modeling the obscure data beyond the limits of existing approaches owing to the parameter q and three real valued membership functions. The accomplished strategy of VIKOR method is established on the major concepts of regret measure and group utility measure to specify the compromise solution. Further, TOPSIS method is another well established multi-criteria decision-making strategy that finds out the best solution with reference to the distances from ideal solutions. In this research study, we propose the innovative and modified versions of VIKOR and TOPSIS techniques using the numerous advantages of q-rung picture fuzzy information for obtaining the compromise results and rankings of alternatives in decision-making problems with the help of two different point-scales of linguistic variables. The procedure for the entropy weighting information is adopted to compute the normal weights of attributes. The q-rung picture fuzzy VIKOR (q-RPF VIKOR) method utilizes ascending order to rank the alternatives on the basis of maximum group utility and minimum individual regret of opponent. Moreover, a compromise solution is established by scrutinizing the acceptable advantage and the stability of decision. In the case of TOPSIS technique, the distances of alternatives to ideal solutions are determined by employing the Euclidean distance between q-rung picture fuzzy numbers. The TOPSIS method provides the ranking of alternatives by considering the descending order of closeness coefficients. For explanation, the presented methodologies are practiced to select the right housing society and the suitable industrial robot. The comparative results of the proposed techniques with four existing approaches are also presented to validate their accuracy and effectiveness.

Extended VIKOR-QUALIFLEX Method Based on Trapezoidal Fuzzy Two-Dimensional Linguistic Information for Multiple Attribute Decision-Making with Unknown Attribute Weight

Considering the advantages of trapezoid fuzzy two-dimensional linguistic variables (TrF2DLVs), which can not only accurately describe the qualitative evaluation but also use qualitative linguistic variables (LVs) to describe the confidence level of this evaluation in the second dimension, this paper proposes a novel method based on trapezoidal fuzzy two-dimensional linguistic information to solve multiple attribute decision-making (MADM) problems with unknown attribute weight. First, a combination weight model is constructed, which covers a subjective weight determination model based on the proposed trapezoidal fuzzy two-dimensional linguistic best-worst method (TrF2DL-BWM) and an objective weight determination model based on the proposed CRITIC method. Then, in order to accurately rank the alternatives, an extended VIKOR-QUALIFLEX method is proposed, which can measure the concordance index of each ranking combination by means of group utility and individual maximum regret value of each evaluation alternative. Finally, a practical problem of lean management assessment for industrial residential projects is solved by the proposed method, and the effectiveness and advantages of the method are demonstrated by comparative analysis and discussion.

The Hierarchical VIKOR Method with Incomplete Information: Supplier Selection Problem

To solve a multi-criteria decision-making problem, many attempts have been made to alleviate difficulties of obtaining precise preference information attributed to time pressure, lack of data and domain knowledge, limited attention and information processing capabilities, etc. Structuring any decision problem hierarchically is known to be an efficient way of dealing with complexity and identifying the major components of the problem. In this paper, we propose the hierarchical VIKOR method that uses incomplete alternatives’ values as well as incomplete criteria weights, extending previous works that consider mostly intervals or fuzzy under a flat structure of criteria. It ranks alternatives using the aggregated scores of group utility and individual regret scores which are computed from the linear programs. To show how to use our proposed method, we exemplified an international supplier selection problem that affects the organization’s sustainable growth.

Geometric consistency of triangular fuzzy multiplicative preference relation and its application to group decision making

The triangular fuzzy multiplicative preference relation (TFMPR) has attracted the attention of many scholars. This paper investigates the geometric consistency of TFMPR and applies it to group decision making (GDM). Firstly, by introducing two parameters, a triangular fuzzy number is transformed into an interval. According to the geometric consistency of interval multiplicative preference relation (IMPR), the geometric consistency of TFMPR is defined. Then, two corresponding IMPRs are extracted from the TFMPR by programming models in the majority case and minority case, respectively. Using the constructed linear programming models, two interval priority weight vectors are obtained from the two extracted IMPRs, respectively. Combining two interval priority weight vectors, a linear programming model is established to derive the triangular fuzzy priority weights. Subsequently, the closeness degrees of alternatives by experts are defined to obtain the group utility indices and individual regret indices of alternatives. Then, the compromise indices of alternatives are calculated considering experts’ compromise attitude. By minimizing the compromise indices of alternatives, a multi-objective programming model is constructed to obtain experts’ weights. By aggregating the individual TFMPRs, the collective TFMPR is obtained to derive the triangular fuzzy priority weights. Using the arithmetic mean values, the ranking order of alternatives is generated. Therefore, a method is proposed to solve GDM with TFMPRs. Finally, a performance evaluation example of precise poverty alleviation is provided to illustrate the advantage of the proposed method.

Social Learning in Multi Agent Multi Armed Bandits

We introduce a novel decentralized, multi agent version of the classical Multi-Arm Bandit (MAB) problem, consisting of n agents, that collaboratively and simultaneously solve the same instance of K armed MAB to minimize individual regret. The agents can communicate and collaborate among each other only through a pairwise asynchronous gossip based protocol that exchange a limited number of bits. In our model, agents at each point decide on (i) which arm to play, (ii) whether to, and if so (iii) what and whom to communicate with.

Push-Sum Distributed Online Optimization With Bandit Feedback.

In this article, we concentrate on distributed online convex optimization problems over multiagent systems, where the communication between nodes is represented by a class of directed graphs that are time varying and uniformly strongly connected. This problem is in bandit feedback, in the sense that at each time only the cost function value at the committed point is revealed to each node. Then, nodes update their decisions by exchanging information with their neighbors only. To deal with Lipschitz continuous and strongly convex cost functions, a distributed online convex optimization algorithm that achieves sublinear individual regret for every node is developed. The algorithm is built on the algorithm called the push-sum scheme that releases the request of doubly stochastic weight matrices, and the one-point gradient estimator that requires the function value at only one point at every iteration, instead of the gradient information of loss function. The expected regret of our proposed algorithm scales as O (T2/3 ln2/3(T)) , and T is the number of iterations. To validate the performance of the algorithm developed in this article, we give a simulation of a common numerical example.

Group decision-making framework using complex Pythagorean fuzzy information

This paper contributes to the expanding literature on VIKOR, a well-known multi-criteria decision-making technique. It is abundantly used to find the compromise solution regarding some significant criteria under different models. The general VIKOR methodology implements the principle that a recommended response must be a feasible solution which is nearest to positive ideal solution having maximum group utility and minimum individual regret. In this article, we propose a new strategy to address multi-criteria group decision-making problems named complex Pythagorean fuzzy VIKOR (CPF-VIKOR) method. It is designed to handle a great deal of vagueness and hesitation which are often present in human decisions. The CPF-VIKOR method allows the linguistic terms to express individual opinions of experts about the performance of alternatives and the weights of the criteria. We combine the individual judgments of experts with the help of complex Pythagorean fuzzy weighted averaging operator. Further, we compute the ranking measure with the help of group utility and regret measures by adjusting the weight of strategy of maximum group utility within the unit interval. We sort the alternatives in an ascending order relative to group utility measure and individual regret measure. Moreover, we demonstrate our proposed method with the help of a flow chart and two numerical examples: one for the selection of the most beneficial renewable energy project in Spain and another for the selection of the most suitable logistic village location in Turkey. Finally, we present the comparative analysis of our proposed method with the CPF-TOPSIS method to prove its validity.

A novel approach for ports’ container terminals’ risk management based on formal safety assessment: FAHP-entropy measure—VIKOR model

Maritime transport, which requires complex, large, and long port systems, is a major system in the world trade, and since such systems face different risks, various methods have been proposed to evaluate port area/operations-related risks and safety. A review of various methods that quantify risks in port areas shows that a specific risk management approach/framework capable of dealing with all threats/hazards is scarce. The present paper that proposes a PRM model and aims at transferring the safety-oriented FSA to a framework-based approach, utilizes an fuzzy analytical hierarchy process–VIKOR combined model in the port container terminal domain. Aiming at modeling all the probable risks, the PRM methodology was proposed by considering different port factors and their mutual impacts. The risk management method proposed in this paper uses the Z-number total utility idea to cope with the intrinsic uncertainty existing in experts’ judgment in port container terminal domains. To adjust the experts-proposed subjective weights by objective weights and to give ranking and prioritization to failure modes on the basis of maximum “group utility” and minimum “individual regret,” the Shannon entropy concept and the fuzzy VIKOR technique have been made used, respectively. To find some risk management evidence at the Iranian port container terminals, results of a related empirical study, validated through a sensitivity analysis, have been compared with the conventional FSA. It has been revealed that the applicability of the conventional FSA method can be improved by applying the proposed subjective–objective ranking method in fuzzy environments.

The Dominance Degree-Based Heterogeneous Linguistic Decision-Making Technique for Sustainable 3PRLP Selection

This study develops a novel dominance degree-based heterogeneous linguistic decision-making technique for identifying the most sustainable third-party reverse logistics providers (3PRLPs) under complex input environments. First, qualitative and uncertain inputs that arise from real-world 3PRLP evaluation process are successfully managed by using linguistic terms, hesitant fuzzy linguistic terms, and probabilistic linguistic term sets with different granularities. Then, the dominance degrees of each 3PRLP related to the other 3PRLPs are calculated based on a new ratio index-based probabilistic linguistic ranking method and the dominance matrix is constructed. Furthermore, to represent the closeness of each 3PRLP to the ideal solution, we propose a sort of measures including the dominance-based group utility measure, the dominance-based individual regret measure, and the dominance-based compromise measure. Accordingly, the selection results of 3PRLPs are obtained according to these measures. Finally, the developed method is applied to a case study from car manufacture industry, and the comparison analysis shows that the proposed method is reliable and stable for dealing with the problem of the 3PRLP selection. The main advantage of the developed method is that it cannot only well avoid the potential loss risks but also balance group utility scores and individual regret scores.

A novel outranking method for multiple criteria decision making with interval-valued Pythagorean fuzzy linguistic information

This paper aim to propose a novel outranking method based on interval-valued Pythagorean fuzzy linguistic set (IVPFLS) to estimate alternatives for decision makers. With the rapid increase of the complexity, the challenges of a group of decision makers, a high degree of uncertainty and conflicting criteria are associated with multiple criteria decision making (MCDM) problems and few studies for these. In this regard, the outranking-VIKOR (O-VIKOR) method with the construction of compromise solution considers “group utility” and “individual regret” in pairwise alternatives. To fully show the compromise outranking relation, the O-VIKOR method allows decision makers reach consensus by mutual concessions when the dominant position from alternatives is extant. Subsequently, we define the credibility formula that constitutes a complementary judgment matrix for devoting to ranking the alternatives more precision. When it is necessary to process the evaluation information of multiple decision makers, the interval-value Pythagorean fuzzy linguistic entropic induced ordered weighted averaging (IVPFLEIOWA) operator is proposed with entropic order-inducing variable which includes a new interval-value Pythagorean fuzzy linguistic entropy for measuring uncertainty to capture the interrelationship among the primary preference of decision makers. Finally, a case study on site selection problem for a manufacturer is presented to illustrate the efficiency of our proposed method and make comparative analysis with other methods.

Some new basic operations of probabilistic linguistic term sets and their application in multi-criteria decision making

This paper is concerned with the operations and methods to tackle the probabilistic linguistic multi-criteria decision making (PL-MCDM) problems where criteria are interactive. To avoid the defects of the existing operations of the probabilistic linguistic term sets (PLTSs) and make the operations easier, we redefine a family of operations for PLTSs and investigate their properties in-depth. Then, based on the probabilistic linguistic group utility measure, the probabilistic linguistic individual regret measure and the probabilistic linguistic compromise measure proposed in this paper, the probabilistic linguistic E-VIKOR method is developed. To make up for the deficiency of the above method, the improved probabilistic linguistic VIKOR method which can not only consider the distances between the alternatives and the positive ideal solution but also consider the distances between the alternatives and the negative ideal solution is developed to solve the correlative PL-MCDM problems. And then a case about the video recommender system is conducted to demonstrate the applicability and effectiveness of the proposed methods. Finally, the improved probabilistic linguistic VIKOR method is compared with the probabilistic linguistic E-VIKOR method, the general VIKOR method and the extended TOPSIS method to show its merits.

An Integrated Multicriteria Group Decision-Making Approach for Green Supplier Selection Under Pythagorean Fuzzy Scenarios

As a critical component in green supply chain activities, green supplier selection modelled as the typical multicriteria group decision-making (MCGDM) problem, has received tremendous attention both from scholars and practitioners. This article aims to advance an integrated approach for precisely addressing this urgent problem under Pythagorean fuzzy (PF) scenario. Firstly, analytic hierarchy process (AHP) is utilized for computing criterion weights that comprehensively reflect the intention of decision makers (DMs). Secondly, extend the Vise Kriterijumska Optimizacija I Kompromisno Resenje (VIKOR) to PF scenario, and apply the newest magnitude comparison method and distance measure of PF sets in the $L_{p} -$ metric equation to accurately acquire the ranking indices, then obtain the different ranks of candidates along with the adjustment of DM's preference value to balance the group utility and individual regret. Thirdly, median ranking method (MRM) is employed to reach a consensus opinion for the differentiated ranks of candidates via the attribute-wise rank and linear programming model. Subsequently, a numerical example for an agri-food company in China is introduced to illustrate the feasibility of our AHP-VIKOR-MRM method. Finally, conduct the comparison with some available MCGDM methods with PF information to interpret the stability and practicability of our presented method.

The Identification of Poverty Alleviation Targets Based on the Multiple Hybrid Decision-Making Algorithms

The poverty alleviation problem as one of the social evaluation applications has long been a major focus of social problems. As the basis and starting step of the poverty alleviation project, it is crucial to accurately identify the targets of poverty alleviation. Therefore, first of all, it is necessary to establish a scientific and reasonable indicators system and then evaluate all the indicator values respectively. However, in the process of data evaluation, we found that it is often hard to decide the unique valuation for some indicators because of the hesitation among different possible valuations in the mind. Different from traditional algorithms only using a single indicator valuation, the paper uses Pythagorean fuzzy sets (PFSs) to keep possible valuations from the positive and negative aspects and it can overcome the hesitation in the data evaluation process to a certain extent. The paper considers the problem of identifying the poverty alleviation targets as a multi-criteria decision making (MCDM) problem and then proposes a modified algorithm to solve the problem on the basis of several traditional algorithms. The algorithm work well and can obtain the maximum group utility and the minimum individual regret at the same time in the following experiments. The optimal poverty alleviation targets have been found and the poverty ranking list has also been obtained through the algorithm.

Optimum Selection of Energy Service Company Based on Intuitionistic Fuzzy Entropy and VIKOR Framework

Energy user's choice of energy service company affects the smooth implementation of energy performance contracting. Energy performance contracting is a new mechanism for energy saving. In the energy performance contracting, the energy user and energy service company cooperate to save energy and share the benefit. One difficulty in actualizing the energy performance contracting is to select the optimal energy service company. However, there are few literatures to analyze the efficient selection mechanism. A government is used as the energy user and the energy service company selection based on intuitionistic fuzzy entropy and VIKOR framework is studied in this paper. A group decision-making method based on intuitionistic fuzzy entropy and VIKOR framework is proposed to solve the multi-attribute group decision-making problem with the unknown decision-makers' weight and attribute weight. First, the attribute synthetic weight is determined by intuitionistic fuzzy entropy weight method and weight coordination coefficient, and expert weight is determined by objective decision information after considering the intuitionistic fuzzy entropy of decision matrix; then, the intuitionistic fuzzy group decision matrix aggregated by experts is obtained through the aggregation of intuitionistic fuzzy weighted average (IFWA) operator, and the improved intuitionistic fuzzy number distance measure is introduced into the solutions of group utility value and individual regret value to make the evaluation results more accurate and reasonable. Finally, the validity and practicability of decision-making method is analyzed and verified with an example, so as to provide a new method and idea for multi-attribute intuitionistic fuzzy group decision-making.

Group Decision-Making Based on the VIKOR Method with Trapezoidal Bipolar Fuzzy Information

The VIKOR methodology stands out as an important multi-criteria decision-making technique. VIKOR stands for “VIekriterijumsko KOmpromisno Rangiranje”, a Serbian term for “multi-criteria optimization and compromise solution”. It has been adapted to sources of information with sundry formats. We contribute to that strand on literature with a design of a new multiple-attribute group decision-making method called the trapezoidal bipolar fuzzy VIKOR method. It consists of a suitable redesign of the VIKOR approach so that it can use information with bipolar configurations. Bipolar fuzzy sets (and numbers) establish a symmetrical trade-off between two judgmental constituents of human thinking. The agents acquire uncertain and vague information in the form of linguistic variables parameterized by trapezoidal bipolar fuzzy numbers. Trapezoidal bipolar fuzzy numbers are considered by decision-makers for assigning the preference information of alternatives with respect to different attributes. Our non-trivial adaptation necessitates several steps. The ranking function of bipolar fuzzy numbers is employed to make a simple decision matrix with real numbers as its entries. Shannon’s entropy concept is applied to evaluate the normalized weights for attributes that may be either partially or completely unknown to the decision-makers. The ordering of the alternatives is obtained by assorting the maximum group utility and the individual regret of the opponent in an ascending manner. For illustration, the proposed technique is applied to two group decision-making problems, namely, the selection of waste treatment methods and the site to plant a thermal power station. A comparison of this method with the trapezoidal bipolar fuzzy TOPSIS method is also presented.

Extension of VIKOR Method for Multi-criteria Decision Making Problem with Triangular Fuzzy Numbers

The VIKOR method was developed for multi-criteria optimization of complex systems. The compromise solutions integrate group utility and individual regret of the opponent, so it has been applied widely into practice. In the past years, very few papers discussed the effect of defuzzification steps on the final decision results. The purpose of the paper is to analyze the information losses by using different defuzzification methods for the multi-criteria decision-making problem in which the criteria value and criteria weights are also triangular fuzzy numbers. Based on the requirement of the VIKOR method, we explain the necessity of defuzzifying triangular fuzzy numbers, then discuss the information losses generated in the process of four operations and compare them regarding two kinds of methods. An extension of VIKOR method is introduced to decrease the information losses. Finally, a numerical example is used to illustrate the applicability of the proposed method.