Multi-criteria Decision-making Applications Research Articles

A Systematic Review of Multi-criteria Decision-making Applications in Reverse Logistics

Multi-criteria decision-making (MCDM) methods have been applied to various reverse logistics problems. In order to develop a reliable knowledge base through accumulating knowledge from previous studies, we conduct a systematic review of the applications of different MCDM methods to different reverse logistics problems. We found 80 relevant papers published in scientist journals, which are application of different MCDM methods to different reverse logistics problems. We classify the literature based on two dimensions problem context and methodology. The results show that recycling and AHP are the most researched problem and methodology respectively. We finally suggest some future research directions with respect to problem context and methodology.

The fuzzy cross-entropy for intuitionistic hesitant fuzzy sets and their application in multi-criteria decision-making

In this paper, the cross-entropy of intuitionistic hesitant fuzzy sets (IHFSs) is developed by integrating the cross-entropy of intuitionistic fuzzy sets (IFSs) and hesitant fuzzy sets (HFSs). First, several measurement formulae are discussed and their properties are studied. Then, two approaches, which are based on the developed intuitionistic hesitant fuzzy cross-entropy, are proposed for solving multi-criteria decision-making (MCDM) problems within an intuitionistic hesitant fuzzy environment. For both methods, an optimisation model is established in order to determine the weight vector for MCDM problems with incomplete information on criteria weights. Finally, an example is provided in order to illustrate the practicality and effectiveness of the proposed approaches.

An engineering approach to human resources performance evaluation: Hybrid MCDM application with interactions

Human performance evaluation is one of the most important fields to analyze for the continuity of an organization. Evaluation files filled by the managers generally end up in dusty folders where no one looks. This decreases the credibility of the evaluators and the process itself. Whereas the management thinks that they are taking the valuable time from the people who can do better things instead of these evaluations. In this paper, we add an engineering point of view to this process by giving a Hybrid Multicriteria Decision Making (MCDM) approach to evaluate employees’ performances working for a same task and explain an efficient way of handling the qualitative and quantitative data simultaneously. The real life situations where performance criteria show interaction will be possible to solve and the different types of interactions will be handled with the proposed hybrid method using Analytical Network Process (ANP) and Choquet Integral (CI) simultaneously. We also give a numerical illustration at the end of the study with the appropriate concluding remarks including the advantages of the proposed method.

Application of multi-criteria decision-making to risk prioritisation in tidal energy developments

This paper presents an analytical multi-criterion analysis for the prioritisation of risks for the development of tidal energy projects. After a basic identification of risks throughout the project and relevant stakeholders in the UK, classified through a political, economic, social, technological, legal and environmental analysis, relevant questionnaires provided scores to each risk and corresponding weights for each of the different sectors. Employing an extended technique for order of preference by similarity to ideal solution as well as the weighted sum method based on the data obtained, the risks identified are ranked based on their criticality, drawing attention of the industry in mitigating the ones scoring higher. Both methods were modified to take averages at different stages of the analysis in order to observe the effects on the final risk ranking. A sensitivity analysis of the results was also carried out with regard to the weighting factors given to the perceived expertise of participants, with different results being obtained whether a linear, squared or square root regression is used. Results of the study show that academics and industry have conflicting opinions with regard to the perception of the most critical risks.

Similarity measures between interval neutrosophic sets and their applications in multicriteria decision-making

An interval neutrosophic set is an instance of a neutrosophic set, which can be used in real scientific and engineering applications. In the paper, the Hamming and Euclidean distances between interval neutrosophic sets INSs are defined and the similarity measures between INSs are proposed based on the relationship between similarity measures and distances. In the applications of the similarity measures, a multicriteria decision-making method is established in interval neutrosophic setting, in which criterion values with respect to alternatives are evaluated by the form of interval neutrosophic values INVs and the criterion weights are known information. We utilize the similarity measures between each alternative and the ideal alternative to rank the alternatives and to determine the best one. Finally, an illustrative example demonstrates the applications of the proposed decision-making method.

Application of Multi-Criteria Decision-Making in Land Evaluation of Agricultural Land Use

The present study was carried out to evaluate agricultural capability of a watershed located in Khuzestan; a province in southern Iran. It is aimed to examine the applicability of Multi Criteria Decision-Making (MCDM) methods in site selection process. Accordingly, the ecological resources of the watershed were initially identified. To specify the criteria required for agricultural land evaluation, Delphi method was applied. After selecting the criteria, they were weighted using Analytical Hierarchy Process (AHP) Method. Weighted Overlay (WO) Method was also used to overlay the map layers in the GIS environment. Afterwards, sensitivity analysis was performed using Weights Sensitivity Analysis (WSA) method to show the impressibility rate of the results against a certain changes in the inputs. The results revealed that out of 6591.2 ha of the total watershed area, 50.8 % has unsuitable potentiality while 27.32 % has a poor suitability for irrigated agriculture. It was also determined that only 6.96 % of the whole study area has a suitable potential for this purpose. Besides, the findings indicated that 23.38 % of the total watershed area is unsuitable for rain-fed farming. the results also showed that 31.78 % and 19.12 % of the entire study area has moderate and high potentials for rain-fed agriculture, respectively. In a general overview, this study could present how MCDM is effective in handling land capability studies.

Spatially-explicit sensitivity analysis for land suitability evaluation

Land suitability evaluation (LSE) is an important step in land-use planning. Using multi-criteria decision-making (MCDM) techniques based on geographic information systems is a flexible and effective approach for this evaluation process. Implementation of sensitivity analysis to validate and calibrate the MCDM can enhance the understanding of the LSE results and assist in making informed planning decisions. The main limitation of sensitivity analysis in MCDM applications is a lack of insight into the spatial dimensions. To address this issue, this paper presents a new framework that incorporates the spatial configuration information from sensitivity analysis for MCDM. The framework consists of a land suitability evaluation and a spatially explicit sensitivity analysis. The sensitivity analysis couples spatial visualization and summary indicators, which include a traditional metric (i.e., the mean of the absolute change rate, MACR) and a novel spatially explicit metric (the Earth Mover's Distance, EMD). The newly reclaimed region of Yili in China was studied as the representative area. We assumed that the weights were the only source of uncertainty and used a one-dimensional sensitivity analysis. This experiment indicated that the expert LSE results for wheat are robust but relatively sensitive in local areas to changes in the weights. Our results confirm that the MACR and EMD can effectively identify sensitive parameters based on various sensitivity aspects. The EMD explores the new information from the spatial dimensions, which differs from traditional methods for sensitivity analysis. This approach provides a suitable framework based on a spatially explicit sensitivity analysis for the effective implementation of MCDM for robust LSE results.

A review of multi-criteria decision-making methods for infrastructure management

In infrastructure management, multi-criteria decision-making (MCDM) has emerged as a decision support tool to integrate various technical information and stakeholder values. Different MCDM techniques and tools have been developed. This paper presents a comprehensive review on the application of MCDM literature in the field of infrastructure management. Approximately 300 published papers were identified that report MCDM applications in the field of infrastructure management during 1980–2012. The reviewed papers are classified into application to the type of infrastructure (e.g. bridges and pipes), and prevalent decision or intervention (e.g. repair and rehabilitate). In addition, the papers were also classified according to MCDM methods used in the analysis. The paper provides taxonomy of those articles and identifies trends and new developments in MCDM methods. The results suggest that there is a significant growth in MCDM applications in infrastructure management applications of MCDM over the last decade. It has also been noted that many decision support tools based on multiple MCDM methods have been successfully used for infrastructure management.

Bharat Tobacco: vendor selection and vendor rating

Subject area Supply chain management and particularly the significance of vendors as a strategic decision making tool. Study level/applicability The case is suitable for use in the following courses: MBA programs with specialisation in operations management where it can be used to teach students the significance of vendor selection and vendor rating in supply chain management (SCM); marketing research in management where it can be used to highlight the concept of multi attribute utility theory (MAUT) and its application; advanced statistics for multi criteria decision making (MCDM); and MBA/post graduate programs in management in strategic management where it can be used to introduce the concept of SWOT analysis and Porter's five forces model. An understanding of business process improvement will enable students get a comprehensive view about the case. Case overview This case showcases the concepts of MCDM and SCM in manufacturing industry. The company wanted to select vendors and rate them in each category of raw materials in order to have a competitive advantage over competitors. Since there are multiple attributes (often contradictory in nature) based on which the vendors would be selected Kaul, Vice-President, Commercial uses multi-attribute utility theory (MAUT) to help solve the problem. The case has implications for manufacturing industry in selecting vendors to meet a raw materials need. Expected learning outcomes The case can be used to understand management concepts such as market research, supply chain management and multi criteria decision making. It can be used to: teach complexities involved in identifying attributes for vendor selection and vendor rating; help understand supply chain management in business process improvement; help students understand the application of MCDM; and help MBA students studying marketing research. The case will also be useful to students in understanding the application of MCDM in operations management. Some knowledge about cigarette manufacturing will help students to realize the depth of the case. Supplementary materials Teaching notes are available for educators only. Please contact your library to gain login details or email support@emeraldinsight.com to request teaching notes.

Material selection using hybrid MCDM approach for automobile bumper

This paper describes an application of multi-criteria decision-making (MCDM) techniques to evaluate optimum material to be employed for manufacturing of automobile bumper. The proposed hybrid MCDM technique involves fuzzy analytical hierarchy process (FAHP) integrated with preference ranking organisation method for enrichment evaluation (PROMETHEE). FAHP is used to compute the criteria weights. PROMETHEE I is used to find out the leaving and entering flows, whereas PROMETHEE II is used to find the total ranking of the material. This study focuses on five alternatives such as polyethylene, polypropylene, acrylonitrile butadiene styrene, polyamide and polystyrene. This study uses six evaluation criteria such as compressive yield strength, flexural modulus, hardness, Charpy impact strength, elongation and cost to select the appropriate material.

Finding Top-k Preferable Products

The importance of dominance and skyline analysis has been well recognized in multicriteria decision-making applications. Most previous studies focus on how to help customers find a set of “best” possible products from a pool of given products. In this paper, we identify an interesting problem, finding top-k preferable products, which has not been studied before. Given a set of products in the existing market, we want to find a set of k “best” possible products such that these new products are not dominated by the products in the existing market. We study two problem instances of finding top-k preferable products. In the first problem instance, we need to set the prices of these products such that the total profit is maximized. We refer such products as top-k profitable products. In the second problem instance, we want to find k products such that these k products can attract the greatest number of customers. We refer these products as top-k products. In both problem instances, a straightforward solution is to enumerate all possible subsets of size k and find the subset which gives the greatest profit (for the first problem instance) or attracts the greatest number of customers (for the second problem instance). However, there are an exponential number of possible subsets. In this paper, we propose solutions to find the top-k profitable products and the top-k popular products efficiently. An extensive performance study using both synthetic and real data sets is reported to verify the effectiveness and efficiency of proposed algorithms.

Skyline distance: a measure of multidimensional competence

Skyline has been widely recognized as being useful for multi-criteria decision-making applications. While most of the existing work computes skylines in various contexts, in this paper, we consider a novel problem: how far away a point is from the skyline? We propose a novel notion of skyline distance that measures the minimum cost of upgrading a point to the skyline given a cost function. Skyline distance can be regarded as a measure of multidimensional competence and can be used to rank possible choices in recommendation systems. Computing skyline distances efficiently is far from trivial and cannot be handled by any straightforward extension of the existing skyline computation methods. To tackle this problem, we systematically explore several directions. We first present a dynamic programming method. Then, we investigate the boundary of skylines and develop a sort-projection method that utilizes the skyline boundary in calculating skyline distances. Last, we develop a space partitioning method to further improve the performance. We report extensive experiment results which show that our methods are efficient and scalable.

A comparative analysis of the DEA-CCR model and the VIKOR method

Data Envelopment Analysis (DEA) introduces a model for weights determination maximizing efficiency of the decision-making units. The primary focus of the DEA model is to compare decision-making units (alternatives) in terms of their efficiency in converting inputs into outputs. The multicriteria decision making (MCDM) method VIKOR uses a common set of weights expressing a decision maker's preferences. In contrast, the CCR model of DEA does not provide a common set of weights that could express the preferences of a decision maker. The weights in MCDM do not have a clear economic significance, but their use provides the opportunity to model the real aspects of decision making, such as the preference structure. A comparison of DEA and MCDM shows that DEA resembles MCDM, but the results differ. In spite of these differences, DEA could be used as a supplement for screening alternatives within MCDM. An application of DEA and MCDM is illustrated by an example of hydropower system planning.

Application of multi-criteria decision-making on strategic municipal solid waste management in Dalmatia, Croatia

The efficiency of providing a waste management system in the coastal part of Croatia consisting of four Dalmatian counties has been modelled. Two multi-criteria decision-making (MCDM) methods, PROMETHEE and GAIA, were applied to assist with the systematic analysis and evaluation of the alternatives. The analysis covered two levels; first, the potential number of waste management centres resulting from possible inter-county cooperation; and second, the relative merits of siting of waste management centres in the coastal or hinterland zone was evaluated. The problem was analysed according to several criteria; and ecological, economic, social and functional criteria sets were identified as relevant to the decision-making process. The PROMETHEE and GAIA methods were shown to be efficient tools for analysing the problem considered. Such an approach provided new insights to waste management planning at the strategic level, and gave a reason for rethinking some of the existing strategic waste management documents in Croatia.

Introducing reliability measures into multi-criteria decision-making

This paper addresses comparing Alternative Designs (ADs) of an engineering project by taking into account fail-safe behaviour of these designs. The methodology of Multi-Criteria Decision-Making (MCDM) is suggested for the selection of the optimal design among available ones. The prime objective of this paper is introducing reliability and availability into the mathematical framework of MCDM. The discussion also covers applying basic elements of Reliability-Based Optimisation (RBO) and utility theory in solving problems of MCDM. The main message is that the mathematical framework of MCDM is sufficiently flexible to adopt probabilistic attributes (characteristics) of ADs. The paper considers intersections of MCDM with methods of reliability theory. Examples of a combined application of MCDM and reliability theory are presented by both the authors together with a third co-author in a paper given in the same issue of the journal.

Towards multidimensional subspace skyline analysis

The skyline operator is important for multicriteria decision-making applications. Although many recent studies developed efficient methods to compute skyline objects in a given space, none of them considers skylines in multiple subspaces simultaneously. More importantly, the fundamental problem on the semantics of skylines remains open: Why and in which subspaces is (or is not) an object in the skyline? Practically, users may also be interested in the skylines in any subspaces. Then, what is the relationship between the skylines in the subspaces and those in the super-spaces? How can we effectively analyze the subspace skylines? Can we efficiently compute skylines in various subspaces and answer various analytical queries?In this article, we tackle the problem of multidimensional subspace skyline computation and analysis. We explore skylines in subspaces. First, we propose the concept of Skycube, which consists of skylines of all possible nonempty subspaces of a given full space. Once a Skycube is materialized, any subspace skyline queries can be answered online. However, Skycube cannot fully address the semantic concerns and may contain redundant information. To tackle the problem, we introduce a novel notion of skyline group which essentially is a group of objects that coincide in the skylines of some subspaces. We identify the decisive subspaces that qualify skyline groups in the subspace skylines. The new notions concisely capture the semantics and the structures of skylines in various subspaces. Multidimensional roll-up and drill-down analysis is introduced. We also develop efficient algorithms to compute Skycube, skyline groups and their decisive subspaces. A systematic performance study using both real data sets and synthetic data sets is reported to evaluate our approach.

Conjoint axiomatization of Min, DiscriMin and LexiMin

In many multi-criteria decision-making applications, the preferential information is of an ordinal nature and appropriate aggregation procedures should be used. In this paper, we build a common axiomatic framework to characterize the “Minimum” procedure as well as two of its refinements, the “DiscriMin” and the “LexiMin”. In practical situations, this axiomatic framework could help to select the best-suited procedure.

A multi-criteria decision-making model and its application in system solution engineering

A multi-criteria decision-making model is presented in terms of system solution engineering applications. However, the model can also be used for many other multi-criteria decision-making applications in general. The model consists of a set of possibility integrals. A possibility integral is a nonlinear overall evaluation of two partial evaluations: the possibility measures of the degree of importance of each subset of all criteria and the function of the degrees of satisfaction of a solution to every criterion. The best system solution can be found by using the model to quantitatively evaluate alternative system solutions for the same set of customer system requirements (criteria). The best system solution is the one that has the highest degree of satisfaction to the requirements. The word “best” implies human judgment or subjectivity that is evolved in a decision-making process. The possibility theory induced from fuzzy sets provides a theoretical foundation for resolving decision-making problems with subjective and/or objective uncertainty. An example demonstrates how to use the model to find the best solution for a system solution engineering problem.

A Sensitivity Analysis Approach for Some Deterministic Multi‐Criteria Decision‐Making Methods*

ABSTRACTOften, data in multi‐criteria decision making (MCDM) problems are imprecise and changeable. Therefore, an important step in many applications of MCDM is to perform a sensitivity analysis on the input data. This paper presents a methodology for performing a sensitivity analysis on the weights on the decision criteria and the performance values of the alternatives expressed in terms of the decision criteria. The proposed methodology is demonstrated on three widely used decision methods. These methods are the weighted sum model (WSM), the weighted product model (WPM), and the analytic hierarchy process (AHP). This paper formalizes a number of important issues on sensitivity analysis and derives some critical theoretical results. Also, a number of illustrative examples and computational experiments further illustrate the application of the proposed methodology.