Multicriteria approval: application of approval voting concepts to MCDM problems

Multicriteria decision making (MCDM) methods generally require information that is difficult and expensive to obtain. It is shown in this paper that given an ordering of criteria by importance, and whether each alternative is above the average evaluation of the alternatives for each criterion, considerable information can be extracted concerning the overall rankings of the alternatives. This is done by recognizing the similarity between criteria in MCDM, and voters in social choice theory. Multicriteria approval, proposed in this paper, is an MCDM adaptation of approval voting which can be used to classify decisions into one of several categories, depending on whether, and the manner in which, a superior alternative can be identified. An exhaustive examination of all possible decision situations of tractable size is made to measure the applicability of multicriteria approval, and the approach is demonstrated in an industrial procurement case. In addition to requiring minimal information from a decision maker, multicriteria approval satisfies several desirable criteria for MCDM techniques. © 1998 John Wiley & Sons, Ltd.     

A non-linear multi-criteria model for strategic fms selection decisions

The strategic decision of selecting an optimal flexible manufacturing system (FMS) configuration is a complicated question which involves evaluating trade-offs between a number of different, potentially conflicting criteria such as annual production volume, flexibility, production and investment costs and average throughput of the system. Recently, several structured multicriteria approaches have been proposed to aid management in the FMS selection process. While acknowledging the non-linear nature of a number of the relationships in the model, notably between batch size and the number of batches produced of each part, these studies used linear simplifications to illustrate the decision dynamics of the problem. These linear models were shown to offer useful analytical tools in the FMS pre-design process. Owing to the non-linearities of the true relationships, however, the trade-offs between the criteria could not fully be explored within the linear framework. This paper builds on the two-phase decision support framework proposed by Stam and Kuula (1991) and uses a modified non-linear multi-criteria formulation to solve the problem. The software used in the illustration can easily be implemented, is user-interactive and menu-driven. The methodology is applied to real data from a Finnish metal product company and the results are compared with those obtained in previous studies.     

Experimental consideration of preference in decision making under certainty

This paper describes an experiment in decision making under certainty with multiple, conflicting objectives and continuous decision variables. Two techniques for analysing such problems are considered: one taken from the paradigm of multicriteria decision making (MCDM), a non-directed approach called the NAIVE technique, and one from the paradigm of multiattribute decision analysis (D/A), the SMART technique. While the two techniques seek and are throught to arrive at the same end—a solution which is in some sense optimal for the decision maker (DM)—the former approach implicitly incorporates DM preferences while the latter approach considers preferences explicitly. The setting is a laboratory study using a sample of university students on a three-criteria problem which is designed to study the extent to which value functions implied/assessed by the techniques are consistent with DMs' holistic ranking of alternatives. Results show that (1) the two techniques of interest show significantly better rank order correlation with holistic judgement compared with other techniques, (2) DMs prefer the non-directed MCDM approach and (3) subjects break down into two groups: those that use assessable value functions when ranking and those that do not. This implies that for small-dimensioned problems DMs may first need to be classified as to the assessability of their value functions before a solution method is chosen.     

Multiple Criteria Decision‐Making in Management Accounting and Control‐State of the Art and Research Perspectives Based on a Bibliometric Study

As an academic discipline as well as in practice, decision support is one of the most important functions of management accounting and control (MAC). Owing to decision settings' increasing complexity, suitable multiple criteria methods are becoming increasingly important for MAC. We, therefore, examine the extent to which certain multiple criteria decision‐making (MCDM) methods are used in the MAC context. In order to do so, we undertook an extensive bibliometric analysis of the management accounting field during the last three decades. The results indicate an increase in the importance of MCDM. Furthermore, recent research activities were classified into different areas of decision‐making within MAC since the majority of publications deal with the areas of strategic management, budgeting and performance management. More specifically, strategy and performance evaluation, strategic planning and the selection of alternatives are the most prominent MCDM applications. Our analysis reveals that the analytic hierarchy process (AHP) is the most popular analytical tool with which to support management in complex decision‐making situations. The results of the study prove that technical MAC literature does not cover a desirable range of MCDM applications and that the AHP, as well as the analytic network process (ANP) are of increasing importance in respect of the international scope of MAC. Therefore, the area of MCDM continues to be an active part of management science research and application, specifically of MAC. Copyright © 2011 John Wiley & Sons, Ltd.     

The Characteristic Objects Method: A New Distance‐based Approach to Multicriteria Decision‐making Problems

Multicriteria decision‐making (MCDM) methods are concerned with the ranking of alternatives based on expert judgements made using a number of criteria. In the MCDM field, the distance‐based approach is one popular method for obtaining a final ranking. The technique for order preference by similarity to the ideal solution (TOPSIS) is a commonly used example of this kind of MCDM method. The TOPSIS ranks the alternatives with respect to their geometric distance from the positive and negative ideal solutions. Unfortunately, two reference points are often insufficient, especially for nonlinear problems. As a consequence of this situation, the final result ranking is prone to errors, including the rank reversals phenomenon. This study proposes a new distance‐based MCDM method: the characteristic objects method. In this approach, the preferences of each alternative are obtained on the basis of the distance from the nearest characteristic objects and their values. For this purpose, we have determined the domain and Fuzzy number set for all the considered criteria. The characteristic objects are obtained as the combination of the crisp values of all the Fuzzy numbers. The preference values of all the characteristic object are determined on the basis of the tournament method and the principle of indifference. Finally, the Fuzzy model is constructed and is used to calculate preference values of the alternatives, making it a multicriteria model that is free of rank reversal. The numerical example is used to illustrate the efficiency of the proposed method with respect to results from the TOPSIS method. The characteristic objects method results are more realistic than the TOPSIS results. Copyright © 2014 John Wiley & Sons, Ltd.     

A Multicriteria Decision‐Making Application to the Conceptual Design of Mechanical Components

Early design is crucial for the success of the final product. In the conceptual design phase, several constraints, criteria, objectives and disciplines have to be considered. To this aim, multidisciplinary optimization has proven effective for the solution of engineering design problems, even in the industrial every‐day practice, to improve and simplify the work of designers in a successful quest of the best compromise solution. In this paper, a multicriteria decision‐making (MCDM)‐based design platform for early optimal design of industrial components is proposed. In a group decision‐making context, the selection of the most suitable component among several possible layouts is performed by means of a group Fuzzy Technique for Order of Preference by Similarity to Ideal Solution approach. Hence, a multi‐objective optimization is performed on the selected component by applying a multi‐objective particle swarm optimization for finding optimal component dimensions. An industrial case study is presented for showing the efficiency of the multicriteria decision‐making‐based design platform, regarding an innovative and low‐cost solution to increase the duration of heel tips in women's shoes. Copyright © 2016 John Wiley & Sons, Ltd.     

The modified star graph and the petal diagram: two new visual aids for discrete alternative multicriteria decision making

Many studies have looked into the provisions of visual aids to multicriteria decision making. However, most of them have separated the display of alternative profiles and criteria weight information into two displays. This makes the analysis of the relationship between the criteria and alternatives and the effect of changing the criteria weights on the decision difficult. In this study, displays that can incorporate the display of both alternative profiles and criteria weight information for discrete alternative multicriteria decision-making problems are examined. The simple additive model is the multicriteria analysis method used. The result is two new visual aids for representing data of multicriteria decision-making problems, the modified star graph and the petal diagram. This paper discusses the two displays and compares their strengths and weaknesses. The results of a preliminary test conducted to evaluate the effectiveness of the displays are also included. © 1998 John Wiley & Sons, Ltd.     

Applications of the MACBETH Approach in the Framework of an Additive Aggregation Model

In measurement theory terminology, MACBETH is an interactive approach for mapping into a real scale the various degrees to which the elements of a finite set possess a property P. The originality of MACBETH's questioning procedure is the possibility of establishing a constructive path towards cardinal measurement in both quantitative and substantive meaningful terms, avoiding the operational problems recognized as a weakness of other procedures. The use of the notion of semantic absolute judgements plays a key role here and the simplicity, interactivity and constructiveness of our approach insert it in the modern paradigms of decision aid. This article illustrates the usefulness of MACBETH as a tool to facilitate decision support, by describing its application in two real public decision situations where we acted as facilitators. Although the cases correspond to quite different decision contexts and problematics and our interventions have addressed diverse issues, they have in common the fact that we conducted both evaluation processes in the framework of an additive multicriteria aggregation procedure. In the first case MACBETH has been used to support the construction of (local) cardinal value functions, while the second illustrates how our approach can serve as a weighting procedure to determine the scaling constants of an additive aggregation model. © 1997 John Wiley & Sons, Ltd.     

Fuzzy MCDM based on the concept of α‐cut

In a fuzzy multiple criteria decision‐making (MCDM) problem, with a hierarchical structure of more than two levels and involving multiple decision‐makers (DMs), to find the exact membership functions of the final aggregation ratings of all feasible alternatives is almost impossible. Thus, ranking methods based on exact membership functions cannot be utilized to rank the feasible alternatives and complete the optimal selection. To resolve the above‐mentioned complexity and to incorporate assessments of all DMs' viewpoints, in this paper a fuzzy MCDM method with multiple DMs, based on the concepts of fuzzy set theory and α‐cut, is developed. This method incorporates a number of perspectives on how to approach the fuzzy MCDM problem with multiple DMs, as follows: (1) combining quantitative and qualitative criteria as well as negative and positive ones; (2) using the generalized means to develop the aggregation method of multiple DMs' opinions; (3) incorporating the risk attitude index β to convey the total risk attitude of all DMs by using the estimation data obtained at the data input stage; (4) employing the algebraic operations of fuzzy numbers based on the concept of α‐cut to calculate the final aggregation ratings and develop a matching ranking method for proposed fuzzy MCDM method with multiple DMs. Furthermore, we use this method to survey the site selection for free port zone (FPZ) in Taiwan as an empirical study to demonstrate the proposed fuzzy MCDM algorithm. The result of this empirical investigation shows that the port of Kaohsiung, the largest international port of Taiwan as well as the sixth container port in the world in 2004, is optimal for the Taiwan government in enacting the plan of FPZ. Copyright © 2005 John Wiley & Sons, Ltd.     

Accounting for Time Preference in Management Decisions: An Application to Invasive Species

Managers of invasive species seek to prevent and mitigate their impact, which vary in the time horizon over which they are realized. Likewise, stakeholders vary in the time horizons they consider relevant. Agricultural impacts might reasonably be considered over two or three decades, although ecologists typically consider environmental impacts over much longer time frames. Although time preference plays a critical role in decision making, it has largely been ignored in multicriteria analyses. In this study, we examine how time has been treated in previous decision analyses of invasive species management, focusing on the differences between multicriteria and economic cost–benefit analyses. We then outline a method for incorporating time preference information into multicriteria decision analyses to ensure that criteria weights remain a faithful representation of the decision maker's preferences. To illustrate how time preference can be elicited for invasive species problems involving both monetary and nonmonetary consequences, we describe a small empirical study we conducted with a small group of experts and managers. By outlining a way to consider time preference information in multicriteria analyses of invasive species management, we hope to facilitate better decision making that is reflective of the decision maker's true preferences. Copyright © 2013 John Wiley & Sons, Ltd.     

Dynamic multi-criteria decision making

Most medium-and long-term decision making in industry and government can be viewed as dynamic multi-criteria decision making (MCDM), in which the decision makers are free to alter the emphasis placed on each objective in the light of developing circumstances. In this paper the problem of time-dependent weights in MCDM is discussed and an analysis of empirical data associated with dynamic decision making is presented.     

Simplified approaches for multicriteria decision making under uncertainty

The problem of uncertainty in the outcome of decisions has tended to be glossed over by many MCDM methods, with the exception of multiattribute utility theory (MAUT). MAUT does, however, require quite complicated preference elicitations and knowledge of the full multivariate distribution of outcomes. Results from a series of simulation studies indicate that the preference orderings of MAUT are only minimally changed when using a simple additive aggregation of marginal utilities, especially in relation to the natural imprecisions inherent in preference elicitation. It is shown in the simulations that by far the most critical aspect of multicriteria decision analysis under uncertainty is not the form of aggregation, but the correct elicitation of marginal utilities which properly represent decision maker preferences over gambles. We relate the results obtained here to other results on the approximation of distributions by three- or five-point discrete distributions, and suggest that the use of deterministic MCDM methods of any form (not necessarily value function techniques), applied to an extended formulation in which each criterion measure is repeated for three or five ‘scenarios’, can be justified.     

Ambiguity aversion: the explanatory power of indeterminate probabilities

Daniel Ellsberg presented in Ellsberg (The Quarterly Journal of Economics 75:643–669, 1961) various examples questioning the thesis that decision making under uncertainty can be reduced to decision making under risk. These examples constitute one of the main challenges to the received view on the foundations of decision theory offered by Leonard Savage in Savage (1972). Craig Fox and Amos Tversky have, nevertheless, offered an indirect defense of Savage. They provided in Fox and Tversky (1995) an explanation of Ellsberg’s two-color problem in terms of a psychological effect: ambiguity aversion. The ‘comparative ignorance’ hypothesis articulates how this effect works and explains why it is important to an understanding of the typical pattern of responses associated with Ellsberg’s two-color problem. In the first part of this article we challenge Fox and Tversky’s explanation. We present first an experiment that extends Ellsberg’s two-color problem where certain predictions of the comparative ignorance hypothesis are not confirmed. In addition the hypothesis seems unable to explain how the subjects resolve trade-offs between security and expected pay-off when vagueness is present. Ellsberg offered an explanation of the typical behavior elicited by his examples in terms of these trade-offs and in section three we offer a model of Ellsberg’s trade-offs. The model takes seriously the role of imprecise probabilities in explaining Ellsberg’s phenomenon. The so-called three-color problem was also considered in Fox and Tversky (1995). We argue that Fox and Tversky’s analysis of this case breaks a symmetry with their analysis of the two-color problem. We propose a unified treatment of both problems and we present a experiment that confirms our hypothesis.     

A convex approach for multicriteria decision making in hierarchical systems

In this paper hierarchical multicriteria optimization problems are addressed in a convex programming framework. It is assumed that the criteria are aggregated into a nonlinear function, which renders the problem nonseparable, in general. The projection of the problem onto the criteria space is used to obtain an equivalent separable problem, solved through a relaxation procedure implemented on basis of a multilevel structure. At the upper level of the structure, the decision making process involves the solution of a multicriteria problem formulated in the criteria space. The solution encountered at the upper level originates a lower level parametric optimization problem with separable structure that can be treated by standard coordination-decomposition techniques. The convergence of the overall procedure is ensured. The paper includes an application of the approach proposed for the control of dynamic systems with linear quadratic structure. © 1998 John Wiley & Sons, Ltd.     

Skills Evaluator: a multicriteria decision support system for the evaluation of qualifications and skills in Information and Communication Technologies

Employees need to acquire new qualifications throughout their lives in order to deal with the multiple changes in the labour market. This knowledge and competences (formally or non-formally acquired) must be identified and evaluated. For that reason, an integrated approach to the evaluation of Information and Communication Technology knowledge and skills is proposed. The multicriteria method that has been developed refers to professionals who wish to be accredited in a particular specialization through the evaluation of their professional experience, studies and vocational training. The aim of this paper is to present the multicriteria decision support system, Skills Evaluator, which brings into effect the aforementioned method. Copyright © 2007 John Wiley & Sons, Ltd.     

The contributions of multi‐criteria decision making to the development of decision support systems subspecialties: an empirical investigation

This study focuses on examining the structure of decision support systems (DSS) research, with a particular emphasis on assessing the contributions of multi‐criteria decision making (MCDM) to the development of each of the DSS subspecialty areas. This study traces how concepts and findings by researchers in the MCDM area have been picked up by DSS researchers to be applied, extended and refined in the development of DSS research subspecialties. In doing so, factor analysis is applied to an author cocitation frequency matrix derived from a large database file of comprehensive DSS literature. This study concludes that researchers in the MCDM area have made crucial contributions to the development of DSS research subspecialties. Copyright © 1999 John Wiley & Sons, Ltd.     

Locating a Waste Treatment Facility by Multicriteria Analysis

We describe an application of multicriteria decision aid to the location of a waste treatment facility in eastern Finland. In Finland, the Act on Environmental Impact Assessment Procedure requires that when the amount of waste to be dealt with in a facility exceeds 20,000 tons per year, the process of environmental impact assessment (EIA) must be performed. In addition, the opinions of citizens and different interest groups need to be heard. Generally, EIA requires many different factors to be dealt with. Therefore the use of some multicriteria decision aid may be helpful to preserve the information obtained through the EIA in the decision-making process. The alternative locations for the facility were considered based on 14 criteria by 28 decision makers. The present paper makes use of the PROMETHEE decision aid, which was found to fit well with certain constraints in this type of problem with multiple criteria and multiple decision makers. © 1997 by John Wiley & Sons, Ltd. J. Multi-Crit. Decis. Anal. 6 : 175–184 (1997) No. of Figures: 2. No. of Tables: 3. No. of References: 18.     

The analytic hierarchy process: An effective tool for a strategic decision of a multidisciplinary research center

The external orientation of academic research centers has a high impact on their internal organization. A multidisciplinary research center of the University of Groningen in the Netherlands is concerned with a strategic, organizational decision impelled by a shift in its external orientation. This decision implies a choice for either an organizational structure based on disciplines or an organizational structure based on the fields of application of research. Due to diverging opinions concerning the desirability of each alternative, a multicriteria decisionmaking approach has been applied. Saaty’s Analytic Hierarchy Process (AHP) has been used to facilitate joint decisionmaking processes by evoking consistent logical foundations and consensus formations. Strategic management has used a forward AHP model to determine the future research activities of this center based on its external orientation. Subsequently, two comparable decisionmaking groups have used a backward AHP model to choose the most appropriate organizational structure, based on criteria for scientific research. Feedback procedures have reduced disagreements and have led to a clear decision for a structure based on application fields of research.