Multi-criteria decision-making in A defensive operation of the guided anti-tank missile battery: An example of the hybrid model fuzzy AHP - MABAC

Abstract: Third-party logistics (3PL) has involved a significant response among researchers and practitioners in the recent decade. In the global competitive scenario, multinational companies (MNCs) not only improve quality of service and increase efficiency, but also decrease costs by means of 3PL. However, the assessment and selection of 3PL is a very critical decision, comprising intricacy due to the existence of various imprecisely based criteria. Also, uncertainty is an unavoidable part of the information in the decision-making process and its importance in the selection process is relatively high and needs to be carefully considered. Consequently, incomplete and inadequate data or information may occur among other various selection criteria, which can be termed as a multi-criteria decision-making (MCDM) problem. Interval rough numbers are very flexible to model this type of uncertainty occurring in MCDM problems. Thus this paper presents a new integrated interval rough number (IRN) approach based on the Best Worst Method (BWM) and Weighted Aggregated Sum Product Assessment (WASPAS) method along Multi-Attributive Border Approximation area Comparison (MABAC) to evaluate 3PL providers. The hybrid IRN-BWM based methodology is used for computing the priority weights of criteria while IRN-WASPAS and IRN-MABAC are employed to achieve the final ranking of 3PL providers. A computational study is performed to illustrate the proposed approaches along with a sensitivity analysis on different sets of criteria weight coefficient values to validate the stability of the suggested methodology. Consequently, a comparative analysis of the obtained ranking results with their crisp and fuzzy counterparts is also conducted for checking the reliability of the proposed approach. The results display stability in ranking of alternative results and prove the feasibility of the proposed approach to handle MCDM problems with IRNs.

Abstract: As the generalization of intuitionistic fuzzy set (IFS) and Pythagorean fuzzy set (PFS), the q-rung orthopair fuzzy set (q-ROFS) has emerged as a more meaningful and effective tool to solve multiple attribute group decision making (MAGDM) problems in management and scientific domains. The MABAC (multi-attributive border approximation area comparison) model, which handles the complex and uncertain decision making issues by computing the distance between each alternative and the bored approximation area (BAA), has been investigated by an increasing number of researchers more recent years. In our article, consider the conventional MABAC model and some fundamental theories of q-rung orthopair fuzzy set (q-ROFS), we shall introduce the q-rung orthopair fuzzy MABAC model to solve MADM problems. at first, we briefly review some basic theories related to q-ROFS and conventional MABAC model. Furthermore, the q-rung orthopair fuzzy MABAC model is built and the decision making steps are described. In the end, An actual MADM application has been given to testify this new model and some comparisons between this novel MABAC model and two q-ROFNs aggregation operators are provided to further demonstrate the merits of the q-rung orthopair fuzzy MABAC model.

Abstract: This paper presents a new approach to the treatment of uncertainty and imprecision in multi-criteria decision-making based on interval rough numbers (IRN). The IRN-based approach provides decision-making using only internal knowledge for the data and operational information of a decision-maker. A new normalized weighted geometric Bonferroni mean operator is developed on the basis of the IRN for the aggregation of the IRN (IRNWGBM). Testing of the IRNWGBM operator is performed through the application in a hybrid IR-DEMATEL-COPRAS multi-criteria model which is tested on real case of selection of optimal direction for the creation of a temporary military route. The first part of hybrid model is the IRN DEMATEL model, which provides objective expert evaluation of criteria under the conditions of uncertainty and imprecision. In the second part of the model, the evaluation is carried out using the new interval rough COPRAS technique.

Abstract: Making a decision in everyday life always comes with uncertainty and responsibility. To reduce the risk to a minumum and in order to make a right decision a person can use methods of multicriteria analysis in combination in fuzzy logic. A married couple, representing decision makers in this case study, have purchased an apartment and it needs to be completely refurbished including outside carpentry. Aim of this study is to select the most suitable manufacturer of PVC carpentry for apartment refurbishing. A total pool of 14 quantitative and qualitative criteria is used as a base for selection of the most suitable of seven available manufacturers. For this case study we will use one of newer methods of multicriteria analysis of fuzzy Evaluation Based on Distance from Average Solution (fuzzy EDAS) method. Having reached the results, an analysis of sensitivity has been conducted showing stability of results where manufacturer number 4 represents an optimal solution in 13 experimental sets out of 14 total.DOI: http://dx.doi.org/10.5755/j01.ee.29.3.16818

Abstract: This study aims to introduce a series of novel distance measures of an intuitionistic fuzzy set and an extended Multi-attributive Border Approximation Area Comparison method to address multi-criteria group decision-making problems. To aggregate the intuitionistic fuzzy information, we propose two aggregation operators, namely, the intuitionistic fuzzy Dombi generalised $$ \lambda $$-Shapley Choquet arithmetical average operator and intuitionistic fuzzy Dombi generalised $$ \lambda $$-Shapley Choquet geometric average operator. These aggregation operators consider the importance of combinations and correlations among combinations of input arguments. Furthermore, an illustrative example of a human resource management problem is presented to verify the effectiveness of the proposed method, and sensitivity and comparison analyses are conducted to demonstrate the technique’s stability and advancements. Finally, conclusions are drawn.

Abstract: The purpose of this paper is to briefly trace the evolution of DEA from the initial publication by Charnes et al. (1978b) to the current state of the art (SOA). The state of development of DEA is characterized at four points in time to provide a perspective in both directions—past and future. An evolution map is provided which illustrates DEA growth during the 17-year period, the timing of the major events, and the interconnections and influences between topics. An extensive DEA bibliography is provided.

Abstract: This paper proves the basic theory of the triangular fuzzy number and improves the formulation of comparing the triangular fuzzy number's size. On this basis, a practical example on petroleum prospecting is introduced.

Abstract: This paper is based on the combination of a Geographic Information System (GIS) and tools or multi-criteria decision making (MCDM) methods in order to obtain the evaluation of the optimal placement of photovoltaic solar power plants in the area of Cartagena (Region of Murcia), in southeast Spain. The combination GIS–MCDM generates an excellent analysis tool that allows for the creation of an extensive cartographic and alphanumeric database that will later be used by multi-criteria methodologies to simplify problems to solve and promote the use of multiple criteria. In GIS two types of criteria will be reflected: constraints or restrictive criteria, and weighting criteria or factors. Constraints or restrictive criteria will make it possible to reduce the area of study by discarding those areas that prevent the implementation of renewable energy plants. These criteria will be obtained from the legislation (planning regulations, protected areas, road networks, railways, waterways, mountains, etc). Weighting criteria or factors will be those which, according to the objective to be reached, influence the ability to solve a concrete alternative. The choice of such criteria is marked by the influence presented to the overall goal; in this case they will be location, geomorphological, environmental and climatic criteria. Through the use of MCDM the criteria or factors mentioned will be weighted in order to evaluate potential sites to locate a solar plant. Analysis and calculation of the weights of these factors will be conducted using Analytic Hierarchy Process (AHP). The assessment of the alternatives according to their degree of adequacy is carried out through the TOPSIS method (Technique for Order Preference by Similarity to Ideal Solution).

Abstract: Application of a new MCDA technique called MABAC.The MABAC sensitivity analysis.Five other MCDA techniques were tested under the same conditions.The MABAC showed stability and other techniques. This paper presents the application of the new DEMATEL-MABAC model in the process of making investment decisions on the acquisition of manipulative transport (Forklifts) in logistics centers. The DEMATEL method was used to obtain the weight coefficients of criteria, on the basis of which the alternatives were evaluated. The selection of criteria for evaluating Forklifts was based on an analysis of available literature. The evaluation and selection of Forklifts was carried out using a new multi-criteria method - the MABAC (Multi-Attributive Border Approximation area Comparison) method. This paper presents a practical application and a sensitivity analysis of the MABAC method. The sensitivity analysis was conducted in three stages. In the first stage, a stability analysis was carried out on the solution reached by the MABAC method, depending on changes made to the weights of the criteria. In the second and third stages, a consistency analysis of the results from the MABAC method was carried out depending on both the changes in the measurement units in which the values of individual criteria are presented and on the formulation of the criteria. The SAW, COPRAS, TOPSIS, MOORA and VIKOR methods were tested under the same conditions. Based on the results obtained, it was shown that the SAW, COPRAS, TOPSIS, MOORA and VIKOR methods do not meet one or more of the conditions set, while the MABAC method showed stability (consistency) in its solutions. Through the research presented in this paper, it is shown that the new MABAC method of multi-criteria decision-making is a useful and reliable tool for rational decision-making.

Abstract: In this paper, locating some warehouses as distribution centers (DCs) in a real-world military logistics system will be investigated. There are two objectives: finding the least number of DCs and locating them in the best possible locations. The first objective implies the minimum cost of locating the facilities and the latter expresses the quality of the DCs locations, which is evaluated by studying the value of appropriate attributes affecting the quality of a location. Quality of a location depends on a number of attributes; so the value of each location is determined by using Multi Attribute Decision Making models, by considering the feasible alternatives, the related attributes and their weights according to decision maker’s (DM) point of view. Then, regarding the obtained values and the minimum number of DCs, the two objective functions are formed. Constraints imposed on these two objectives cover all centers, which must be supported by the DCs. Using Multiple Objective Decision Making techniques, the locations of DCs are determined. In the final phase, we use a simple set partitioning model to assign each supported center to only one of the located DCs.