Multicriteria decision making

We study the paper of Xu [Z. Xu, On consistency of the weighted geometric mean complex judgement matrix in AHP, European Journal of Operational Research 126 (2000) 683–687] for the group consistency in analytic hierarchy process of multicriteria decision-making. The purpose of this note is threefold. First, we point out the questionable results in this paper. Second, for three by three comparison matrices, we provide a patchwork for his method. Third, we constructed a counter example to show that in general his method is wrong. Numerical examples are provided to illustrate our findings. If there are four or more alternatives, then we may advise researchers to ignore his results to avoid questionable estimation of group consistency.

In this paper we develop a framework for the study of financial equilibrium in the case of sectors in the economy, each of which is faced with two objectives/criteria in his portfolio selection decision making. In particular, we first present the bicriteria decision model of an individual financial sector, who seeks an optimal portfolio composition, given that the wishes to

In recent years, several authors have highlighted the merits of the Cost-Effectiveness Analysis (CEA), e.g., compared to Cost-Benefits Analysis (CBA), particularly for small projects appraisal (e.g., revamping or extraordinary maintenance interventions) and when the impacts of the project are difficult to value or quantify in monetary terms. CEA is a quite consolidated technique, typically applied in practice when one specific impact prevails over the others. This research extends the concept of CEA to a multi-dimensional decision-making context, outlining a methodological framework that includes several criteria to assess the impacts of railway station revamping in urban contexts. The proposed method has already been applied for the project appraisals of five railway stations in Italy; this paper presents the application to a case study representing the typical configuration of a medium-sized Italian railway station. Results have shown that the proposed approach is a valid tool for both designers and infrastructure managers for prioritizing railway station investments in the presence of multiple strategic objectives that also conflict with each other. A multi-dimensional CEA can provide, in a communicative, lean, and effective way, the information on investment costs and the impacts that different policies, layouts, and technological solutions would have, creating the basis for a more transparent debate on resource allocation priorities. Finally, results have shown that the CEA is not only a method for project assessment, but also a tool for improving and directing the design towards the identification of interventions that allow the achievement of the key objectives set ex ante.

We describe a project on the classification of publications in the field of multiple criteria decision making (MCDM). Problems in defining and demarcating this field and its literature are discussed. We present the chosen approach of a classification based on a keyword system and propose two ways of its usage. One is based on a printed form. The other approach utilizes a database which allows an interactive information retrieval.

This paper deals with the basic ideas and implementation of an object-oriented decision support system (DSS), especially for multiple criteria decision making (MCDM). There are various ways of integrating different MCDM methods in a DSS. One approach is the interactive application of different methods by means of an integrative user interface. Integration can also be achieved by utilizing neural networks and similar concepts. Neural network-based DSS are able to combine different methods and to learn from historical decision making. They are able to answer questions like these: What method should be used? How can the parameters be adjusted? Is it useful to apply different methods and to aggregate their results to a compromise solution? And how should this be done?

In the object-oriented implementation concept decision making problems and methods like neural networks and MCDM methods are represented by objects. A class hierarchy of different problems and methods is presented. Each problem can be linked with a method which can solve it. A method can be linked with another method (meta method) which provides a learning strategy. Learning strategies work by applying the methods on some input problems and by comparing the calculated results with some reference results. The relationship between problems, methods, and learning methods is illustrated by an example.

Multi-criteria analysis (MCA), in the literature also known under the names of multiple-criteria decision-making (MCDM), multiple-criteria decision analysis (MCDA), multi-objective decision analysis (MODA), multiple-attribute decision-making (MADM) or multi-dimensional decision-making (MDDM), comprises various classes of methods, techniques and tools, with different degrees of complexity, that explicitly consider multiple objectives and criteria (or attributes) in decision-making problems. Since the late 20th century, MCA methods have ignited an increasing interest amongst researchers and practitioners working in a number of fields.
Whereas a number of articles, books and manuals have been written on the subject, the large majority of these are either too technical or overly simplistic. The former type of publications, on the one hand, is hardly readable and comprehensible for non-specialists. The latter pieces of work, on the other hand, tend to ignore many critical aspects of MCA and contribute to the diffusion of practices that are fundamentally flawed. This paper represents an attempt to find a middle ground between those two positions. Its main purpose is to help students, academics, but also practitioners and all those approaching this field of knowledge for the first time to gain insight into the key features of MCA with the view to enabling them to access more complex textbooks in the future. The paper also offers practical guidance regarding the fundamental tasks required to develop basic, yet rigorous multi-criteria frameworks and effectively apply them to different types of decision-making situations and problems. This constitutes the first foundational step for eventually mastering more rigorous and elaborated MCA techniques. Finally, this paper also seeks to discuss the potential advantages and limitations of MCA by adopting, as far as possible, a balanced and neutral perspective so as to break down clichés and false beliefs on the subject.

The use of chemicals and abrasives for highway winter maintenance operations is an essential strategy for ensuring a reasonably high level of service, yet the performance of such materials has to be balanced with their potential negative impacts on motor vehicles,  transportation infrastructure and the natural environment. In this context, this work presents a comprehensive and quantitative evaluation of snow and ice control materials  currently used by various Idaho Transportation Department districts for highway maintenance operations, including: rock salts (mainly solid sodium chloride), IceSlicer products (solid sodium chloride with trace amounts of other chlorides), and salt brines. The analysis has been enabled by the utilization of existing lab and field test data along with reasonable assumptions, in the effort to identify environmentally sustainable materials for  winter highway operations. Despite its caveats, this case study is the first attempt to incorporate the most up-to-date information into a multi-criteria decision making framework for the data-driven, holistic examination of various snow and ice controlmaterials used by a maintenance agency.

Shi, X., Jungwirth, S., Akin, M., Wright, R., Fay, L., Veneziano, D., Zhang, Y., Gong, J., Ye, Z.  Evaluating Snow and Ice Control Chemicals for Environmentally Sustainable Highway Maintenance Operations. ASCE Journal of Transportation Engineering, 2014, 140(11), DOI: 10.1061/(ASCE)TE.1943-5436.0000709.

Use of engineering judgement in design and production of quality product is inevitable. Thus, design optimization is important in development of efficient engineering products. Failure to
identify important design criteria and estimate their associated significance in design and development of an engineering system can result to design, manufacturing, assembly and operating errors.
Therefore, vital design criteria of an engineering product need to be identified and their various level of importance (i.e. weights) revealed using powerful engineering tool. To address this challenge, an Analytical Hierarchy Process (AHP) methodology was employed. The technique was adopted in weight estimation of the wheelchair design criteria such as manufacturing cost (MC), availability of material (AM), reliability (R), nature of environment to be used (NEU), efficiency (E) and anthropometry (A). Experts judgement were employed in the pairwise comparison of the criteria to facilitate the revealing of the criterion with higher weight and the one with lower weight using the mechanism of
the AHP technique. A criterion with higher weight is more important than the one with lower weight and vice versa. The illustrative case study revealed that the AHP technique is a viable tool for weight estimation of the wheelchair design criteria.

This article describes a foundation for modelling generic cognitive structures, under the heading nomology, sometimes known as the “science of the processes of the mind”.  It proposes some principles and axioms that are consistent with the evidence in management systems used in business practice.  It then reviews previous research about nomology in philosophy, science and the humanities.  It shows that the main issue preventing the completion of the foundation of nomology has been the lack of an explanation of the relationship between the objective “nom” part of decision-making as in economics and the subjective “ology” part as in psychology.  It resolves this problem by showing that there are four main objective activities: proposition, perception, pull and push, and for subjective decisions the pull activity becomes redundant.  It then describes cognitive structures for committing oneself, convincing others, and adjusting, and shows examples of them from practice.  It next describes tests in multi-criteria decision-making and in China and Chinese culture to validate that the results are truly generic.  It asserts that nomology will be useful in providing a rigorous foundation for criteria structures in multi-criteria decision-making, and beyond into wider fields, especially those that combine subjective and objective aspects such as in conflict, inter-cultural and inter-disciplinary studies, ethics, and group decision-making.

In this paper we consider the basic ideas, the implementation, and the application of an object-oriented decision support system (DSS), especially for multiple criteria decision making (MCDM). One main idea of the DSS is to utilize the features of different MCDM methods by integration. We discuss several approaches of integration esp. the combination of methods, the use of neural networks, and a generalization of network-like structures.

Information acquisition is an essential part for any DSS. Beside aspects of interactive data entry, we discuss the utilization of historical data (especially from former decisions) for learning. By doing so the parameters of a method, some methods, or a network of methods can be tuned and we can answer questions like: Which method should be used? How can the parameters be adjusted? Is it useful to apply different methods and to aggregate their results to build a compromise solution? And how should this be done?

This article uses a discrete multicriteria method based on the Prospect Theory TODIM -Interactive and Multicriteria Decision Making- such as support for decision making, applied to a casting company that has its plant´s capacity saturated and a permanent list of manufacturing orders backward.

The objective was to prioritize the manufacturing orders that would form the weekly planning considering the plant capacity as a constraint.

The application of TODIM proved to be a suitable tool for the sort of the alternatives according to criteria determined by people in charge, based on motivation, personal desires and weight in the decision making process.

Intersections are critical places which experience high levels of accidents due to the availability of vehicle movements from different directions. Therefore, there is a need to understand the factors that significantly contribute to injuries at such places. These factors can fall under different dimensions in traffic safety such as environmental conditions, road user behavior, traffic police enforcement, road design and crash characteristics. The paper will analyze the factors related to crash characteristics and traffic signal operation that affect the likelihood of accident severity located at intersections. The data for intersection accidents in Abu Dhabi from 2013 to 2016 were used in this analysis. Ordinal logistic model was considered for the analysis to account for the ordinal nature of severity levels. Several diagnostics tests of the model were preformed such as parameters evaluation, overall model evaluation and prediction accuracy. For parameter evaluation, out of 11 independent variables, 6 were non-significant and dropped from the model. Most of the non-significant variables were related to the driver-at-fault details. The results of the final model showed an overall good fit based on a p-value of less than 0.05, as well as a good accuracy of prediction 84.8%. Finally, odds ratios were estimated to interpret the final results of the model.

Multicriterion Decision-Making (MCDM) can be perceived as a process of evaluating real-world situations based on various qualitative/quantitative criteria in certain/uncertain/risky environments in order to find a suitable course of action/choice/strategy/policy among the several available options.

This book concentrates on the basic principles of multicriterion analysis and acquaints the reader with the recent trends in MCDM analysis. It explains the basics of Structured Decision-Making (SDM) and describes the various features of traditional optimization methods such as linear and non-linear programming, and dynamic programming, as well as non-traditional optimization methods such as genetic algorithms, differential evolution, and simulated annealing and quenching.

The text elaborates the normalization methods, weight estimation methods and multiobjective optimization methods both in traditional and non-traditional environments. Classification approaches with cluster validation indices, discrete MCDM methods both in deterministic and fuzzy approach and group decision-making methods are discussed in detail. Advanced topics in decision-making such as data envelopment analysis, Taguchi methodology, ant colony optimization, and particle swarm optimization are also covered.

In addition, the book includes many case studies for better comprehension of the procedures involved in the methods.

KEY FEATURES :

Introduces relevant software to keep the students updated and aware of its potentiality and applicability in multicriterion analysis.

Includes a summary at the end of each chapter to facilitate quick revision of the key learning points.

Provides a number of solved problems to enable students to acquire a clear understanding of the concepts and methods discussed.

Offers several problems at the end of each chapter with answers to help students develop problem-solving skills.

PowerPoint presentations for each chapter are available for instructors.

This book is designed for undergraduate and postgraduate courses in operations research, optimization, soft computing, fuzzy logic and other related courses in engineering and management programmes. It will also be useful to researchers and professionals working in the fields of operations research and management studies.

Actualmente existen muchas técnicas de evaluación que auxilian en el proceso de selección de proveedores, sin
embargo no existe consenso sobre cuál de ellas es mejor que otra o bajo qué circunstancias usarlas. En este artículo se
reporta un caso de estudio, donde un conjunto de proveedores son evaluados mediante la técnica MOORA. El problema consiste en seleccionar un proveedor de un componente electrónico usado en un subensamble automotriz y los atributos evaluados son el precio, la calidad del servicio por parte de proveedor, la administración y organización del proveedor y la tecnología que posee en sus procesos de producción. Después de la evaluación se eligió al mejor proveedor y esta técnica ha sido usada en la selección de proveedores de otros componentes.

Determination of subjective weights, which are based on the opinions and preferences of decision-makers, is one of the most important matters in the process of multi-criteria decision-making (MCDM). Step-wise Weight Assessment Ratio Analysis (SWARA) is an efficient method for obtaining the subjective weights of criteria in the MCDM problems. On the other hand, decision-makers may express their opinions with a degree of uncertainty. Using the symmetric interval type-2 fuzzy sets enables us to not only capture the uncertainty of information flexibly but also to perform computations simply. In this paper, we propose an extended SWARA method with symmetric interval type-2 fuzzy sets to determine the weights of criteria based on the opinions of a group of decision-makers. The weights determined by the proposed approach involve the uncertainty of decision-makers' preferences and the symmetric form of the weights makes them more interpretable. To show the procedure of the proposed approach, it is used to determine the importance of intellectual capital dimensions and components in a company. The results show that the proposed approach is efficient in determining the subjective weights of criteria and capturing the uncertainty of information.

Abstract: Integration of current Virtual Learning Environment (VLE) system with the Near Field Communication (NFC) technology provides Ubiquitous Learning Environment (ULE) in education. The utilization of NFC technology in U-Learning concept will help to improve accessibility and encourage collaborative learning methods in the education sector. In this paper, we conduct a study to investigate eleven (11) adoptions factors of U-Learning with NFC and ranking them using Analytical Hierarchy Process (AHP) a multicriteria decision-making (MCDM) approach. We also utilized Technology Acceptance Model (TAM), Technology Readiness (TR), and combination of TAM and TR (TRAM) as theoretical framework. We have identified TRAM as the best tool based on literature review and utilized the theory to propose an NFC-Enabled Ubiquitous Technology model. The model was utilized to design a questionnaire for survey about user acceptance. Results from the online survey were analyzed using AHP in an absolute measurement approach method. Results from AHP show that optimism is the most influencing factor in adoption of U-Learning using NFC technology followed by innovativeness and accessibility. Finally, this paper contributes in designing an NFC research model.

According to the European Railway Agency in the European Union every year on railway level crossings (RLC) occurs over 1200 traffic accident in which life loses more than 400 people. In addition to the tunnel and specific locations that are identified as black spots on the roads, RLC have been identified as potential weak points in road infrastructure that significantly jeopardize traffic safety. In Serbia exists about 2350 RLC, one of which is part the secured by systems of active and passive safety (traffic signs, light signals, sound signals, barriers, etc..). Insurance RLC is a material expenditure. The RLC selection process for installation of security equipment accompanied by a greater or lesser degree of criteria vagueness that are necessary for making the relevant decisions. For exploitation these uncertainties and vagueness in this paper was used fuzzy logic. This paper presents the application of a new method of multi-criteria decision-making (Multi-Atributive Real-Ideal Comparative Analysis - MARICA), which represents support in the selection process for RLC to invest in safety equipment. Identified are eight criteria that influence the investment decision. MARICA method was tested on the example of choice of eight RLC for investing in safety equipment.
Keywords: mathematical decision making model, Multicriteria decision making, MARICA, DEMATEL

Selection of appropriate subcontractors for outsourcing is very important for the success of construction projects. This can improve the overall quality of projects and promote the qualification and reputation of the main contractors. The evaluation of subcontractors can be made by some experts or decision-makers with respect to some criteria. If this process is done in different time periods, it can be defined as a dynamic multi-criteria group decision-making (MCGDM) problem. In this study, we propose a new fuzzy dynamic MCGDM approach based on the EDAS (Evaluation based on Distance from Average Solution) method for subcontractor evaluation. In the procedure of the proposed approach, the sets of alternatives, criteria and decision-makers can be changed at different time periods. Also, the proposed approach gives more weight to newer decision information for aggregating the overall performance of alternatives. A numerical example is used to illustrate the proposed approach and show the application of it in subcontractor evaluation. The results demonstrate that the proposed approach is efficient and useful in real-world decision-making problems.

Based on the limitations of traditional procurement, this study uses analytical network process (ANP) for contractor selection. Using extensive literature review, best value (BV) contributing factors are identified. Experts are involved to get their feedback for shortlisting the identified factors. An ANP-based decision support system has been developed using data collected through a detailed questionnaire survey in the local construction industry for evaluating the selection process. Further, five case studies of completed road construction projects have been used to validate the decision support system. The findings indicate that in almost all the cases, the traditional procurement system, owing to its stringent prequalification measures, subliminally took into consideration the overall value proposition, and only one case study showed anomalies for which detailed reasoning is deliberated. This highlights the tendency of practitioners to overweigh the cost-based criteria, despite an established significance of other factors, treating the intangible value factors of quality, health and safety, environmental impact, etc. as less important. It reflects that the local construction industry attaches marginal value to qualitative factors. The construction industry will benefit from implementation of BV procurement system and a prolonged exposure may help improve its value system to realize the contribution of non-cost-based factors.

Contracts are designed to govern the relations between business partners and allocate risk among them, yet they cannot mitigate all risks; hence, dispute resolution mechanisms have been developed to assist. According to research, arbitration is considered one of the most efficient legally binding dispute resolution mechanisms. Since initiating an arbitration case against business partners often severs the business relationship between them, predicting the arbitrator's decision becomes valuable to the arbitrating parties. To do so, arbitration prediction models are suggested in this paper through modeling the arbitrator's award in two stages: evidence admissibility and evidence evaluation. While arbitrators currently admit evidence in a relatively unsystematic way, this proposed admissibility framework systemizes the current practice by preserving its subjectivity, yet aligning it with the widely deployed rules of arbitration. This research further proposes an evidence evaluation model, providing a rapid answer to the famous commercial arbitration battle, discovery. While the current arbitrators' practice in allowing discovery is not systematic, the proposed optimization model is a tool that could systematically assist arbitrators trading between the arbitration key characteristic, efficiency, and justice. This is achieved by assigning weights to evidence parameters such as sufficiency and credibility, which in turn provide numerical measures to reduce the decision's subjectivity.

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 centres. 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 wss 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.

Industrial robots have been increasingly used by many manufacturing firms in different industries. The selection of robots for a particular application and manufacturing environment is a difficult task for decision makers. It has become more and more complicated due to increase in complexity, advanced features and facilities that are continuously being incorporated into the robots by different manufacturers. The decision maker needs to identify and select the best-suited robot in order to achieve the desired output with respect to many criteria. In the decision-making process, we usually confront with ambiguity and uncertainty for evaluating the criteria weights and alternatives of the problem. Interval type-2 fuzzy sets which are characterized by an interval membership function can provide us with more degrees of freedom to represent the uncertainty of the real-world problems. This paper presents a multi-criteria group decision-making approach for robot selection in the context of type-2 fuzzy sets. We propose a method based on Vlsekriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method with interval type-2 fuzzy numbers to handle this problem. The best alternative (robot) is selected in the developed method according to both the ideal and the nadir solutions without defuzzification. An example with eight alternatives (robots) and seven commonly used criteria is used to illustrate the proposed method. We compare the results with some existing methods to show the validity of the extended method. Seven sets of criteria weights and the Spearman correlation coefficient are also utilized for analyzing the stability of the proposed method. It is observed that the obtained rankings of the proposed method are relatively consistent with the other methods and have good stability in different criteria weights.