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.     

Determining the implementation order of a general plan by using a multicriteria method

We describe a real-life application of a new multicriteria method in the context of assisting the decision-making for a general plan in the municipality of Kirkkonummi in Uusimaa, Finland. At the time our group started working on the problem, a proposal for an overall plan had already been completed, but the order in which different regional parts of the plan should be implemented needed to be considered based on the environmental impact assessment (EIA) procedure. The EIA procedure generated a large amount of data about the different impacts of the alternatives. For this group decision making problem we developed the SMAA-3 decision support method which does not require any explicit preference information from the decision makers during the procedure. The uncertainty of the basic data is modelled using ELECTRE III-type pseudo-criteria with preference and indifference thresholds. © 1998 John Wiley & Sons, Ltd.     

Group decision as a twice multicriteria optimum problem

This paper studies the problem of aggregation of preferences, preserving the multicriteria nature of the individual decision process. The resulting group decision problem is in effect a twice multicriteria optimum problem. We give a structural theory for the efficient set of this optimum problem. Moreover, on the basis of this theory we study the relationships between optimality, consensus and evaluation. We confirm the pathological nature of aggregation of preferences, but in a new setting and with a different meaning.     

Getting Students to Choose to Do More Work: Evidence of the Effectiveness of the Interspersal Procedure

College students were exposed to two sets of mathematics assignments. For each set students were given an experimental and a control assignment. The control assignments contained 15 three-digit by two-digit target problems. The experimental assignments contained 18 similar target problems as well as six one-digit by one-digit multiplication problems interspersed after every third target problem. In the first assignment set, students were asked to work each assignment for 5 minutes. Although the experimental assignments contained more target problems, results showed that significantly more students chose the experimental assignment and rated it as less difficult and as requiring less effort to complete. In the second assignment set, students were asked to complete both assignments. Again significantly more students rated the experimental assignment as being less difficult and as requiring less effort to complete. Although more students chose the experimental assignment for homework, this difference was not significant. Discussion focuses on using the interspersal procedure to enhance students' perceptions of assignments and alter their choice behavior.     

The problem of classification of personnel

The personnel classification problem arises in its pure form when all job applicants must be used, being divided among a number of job categories. The use of tests for classification involves problems of two types: (1) problems concerning the design, choice, and weighting of tests into a battery, and (2) problems of establishing the optimum administrative procedure of using test results for assignment. A consideration of the first problem emphasizes the desirability of using simple, factorially pure tests which may be expected to have a wide range of validities for different job categories. In the use of test results for assignment, an initial problem is that of expressing predictions of success in different jobs in comparable score units. These units should take account of predictor validity and of job importance. Procedures are described for handling assignment either in terms of daily quotas or in terms of a stable predicted yield.Address of the President of the Division on Evaluation and Measurement of the American Psychological Association, delivered at Denver, Colorado, September 9, 1949.     

When patients contribute to the choice of treatment.…

To explore an alternative solution more appropriate to clinical standards than random assignment, 42 mothers consulting for a functional (sleep, feeding) or behavior problem of their infant were given the choice between two forms of mother–infant psychotherapy (Psychodynamic or Interaction Guidance). Clinicians, blind to mother's choice, followed a systematic indication procedure and provided a therapeutic recommendation. Results revealed a very high agreement between mother's choice and therapists' recommendation. Examination of patient and pretreatment variables showed no major differences between the two groups resulting from a choice of treatment procedure. This procedure proved to ensure internal validity of the data and was also able to guarantee external validity. Discussion focuses on the methodological and clinical implications of the findings that support the consideration of the patient as an active participant to his/her treatment. © 1998 Michigan Association for Infant Mental Health     

An approach to the problem of differential prediction

A procedure for maximizing selective efficiency is developed for application to situations in which it is desired to select from a single group of applicants for several possible assignments. The problem of comparable units for the several criteria whose values must be compared to each other for differential assignment purposes is discussed. It is demonstrated that, assuming linear regressions, maximal selection is obtained if individuals in any given assignment are differentiated from those rejected according to critical rejection scores on the multiple weighted sum of the predictors and from another possible assignment by critical difference scores which are merely the differences between the two critical rejection scores. Since the relationships just indicated give no way of determining the magnitude of the critical scores required to select the required number of persons for each assignment, a successive approximation procedure for accomplishing this purpose has been devised and a computational example is worked out.The opinions expressed are those of the author and are not to be construed as official or as those of the War Department.     

Surrogate‐assisted multicriteria optimization: Complexities,prospective solutions,and business case

Complexity in solving real‐world multicriteria optimization problems often stems from the fact that complex, expensive, and/or time‐consuming simulation tools or physical experiments are used to evaluate solutions to a problem. In such settings, it is common to use efficient computational models, often known as surrogates or metamodels, to approximate the outcome (objective or constraint function value) of a simulation or physical experiment. The presence of multiple objective functions poses an additional layer of complexity for surrogate‐assisted optimization. For example, complexities may relate to the appropriate selection of metamodels for the individual objective functions, extensive training time of surrogate models, or the optimal use of many‐core computers to approximate efficiently multiple objectives simultaneously. Thinking out of the box, complexity can also be shifted from approximating the individual objective functions to approximating the entire Pareto front. This leads to further complexities, namely, how to validate statistically and apply the techniques developed to real‐world problems. In this paper, we discuss emerging complexity‐related topics in surrogate‐assisted multicriteria optimization that may not be prevalent in nonsurrogate‐assisted single‐objective optimization. These complexities are motivated using several real‐world problems in which the authors were involved. We then discuss several promising future research directions and prospective solutions to tackle emerging complexities in surrogate‐assisted multicriteria optimization. Finally, we provide insights from an industrial point of view into how surrogate‐assisted multicriteria optimization techniques can be developed and applied within a collaborative business environment to tackle real‐world problems.     

Estimation of Group Priorities and Value of Information

In this paper, we present a Bayesian approach to model uncertainty about a group's priorities in a multicriteria evaluation problem and develop a methodology to quantify amount of information provided by a sample of priorities. In so doing, we discuss how the quantification of the information content can be used to decide to elicit additional priorities from the group. We illustrate the implementation of our approach and discuss additional insights that it provides using real‐life data from an academic department's priority analysis. Copyright © 2013 John Wiley & Sons, Ltd.     

R&D Project Selection: A Decision Process Approach

The fundamental decision problem of an R&D firm is to select projects in which to invest. Most reported models dealing with this subject use sophisticated mathematical models maximizing specific attributes of the projects without dealing with the underlying motivation of the decision maker. This paper summarizes a successful application of a decision-making process involving multicriteria in the selection of R&D projects in the Ecogen Israel Partnership. We emphasize the structure of the decision problem, with the main goal of helping the decision maker to better understand the nature of his problem. We systematically generate the objective hierarchy of the decision maker, including his main criteria, subcriteria attributes and alternatives. The ‘best’ alternative can then be found using most interactive procedures found in the literature. As the decision maker is totally involved in the entire decision-making process he is better able to understand his problem and preferences.     

Varying Problem Effort and Choice: Using the Interspersal Technique to Influence Choice Towards More Effortful Assignments

College students were exposed to two pairs of mathematics assignments. Assignment Pair A included a high-effort assignment containing 18 long three-digit × two-digit (3×2) multiplication problems with all numerals in each problem being equal to or greater than four and a moderate-effort assignment that contained nine long problems and nine interspersed moderate 3×2 problems with numerals less than four. Assignment Pair B contained similar assignment sheets, the exception being that the high-effort assignment contained six additional one-digit × one-digit (1×1) problems interspersed following every third 3×2 problem. After working on each assignment pair, students ranked assignments and chose a new assignment for homework. Analysis of Assignment Pair A revealed that students overwhelmingly preferred the moderate-effort assignment. Analysis of interaction effects showed that when additional brief problems were added to the high-effort assignments, the proportion of students who chose the high-effort assignment for homework and ranked it as being less difficult, time consuming, and effortful increased significantly. Results support previous research on effort and choice and the hypothesis that a completed discrete problem may serve a reinforcing stimulus.     

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.     

Effects of Interspersing Rate on Student Preferences for Mathematics Assignments

This study investigated the extent to which interspersing effects are consistent with the effects of reinforcement on predicting students preferences for mathematics assignments. Students were exposed to 4 pairs of assignments. Each assignment pair contained a control assignment with 15 problems requiring multiplication of a three digit number by a two digit number, and an experimental assignment consisting of 15 similar multiplication problems plus additional brief one-digit by one-digit multiplication problems interspersed at four different rates (i.e., no interspersing, every other, every third, or every fifth problem) across assignment pairs. Performance data were collected for accuracy, total problem completion rate and target problem completion rate. In addition to performance data, students were asked to rate each assignment with regard to relative difficulty, time, effort to complete, and preference between assignments for homework. Results suggest that although interspersing rates do not affect accuracy, they do affect problem completion rate, and student preferences for academic assignments. Discussion focuses on interspersing rate and schedules of reinforcement with emphasis on both applied and theoretical implications.     

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.     

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.     

Decisionarium ‐ aiding decisions,negotiating and collecting opinions on the web

Decisionarium ( www.decisionarium.hut.fi ) is the first public site for interactive multicriteria decision support with tools for individual decision‐making as well as for group collaboration and negotiation. Web‐HIPRE ( www.hipre.hut.fi ) supports value tree and AHP analysis including group models. The RICH methodology ( www.rich.hut.fi ) allows the decision maker to provide incomplete ordinal preference statements when considering the relative importance of attributes in a value tree. Opinions‐Online ( www.opinion.huf.fi ) is a platform for surveys voting and group collaboration. There are different ways for voting, multiattribute scoring, surveys as well as interactive viewing of the results. Joint Gains ( www.jointgains.hut.fi ) applies the method of improving directions to support multiparty negotiations in a multicriteria setting. Smart Swaps offers an implementation of the even swaps procedure ( www.smart‐swaps.hut.fi ). All of the tools above are web‐based, so global interaction is natural and links can be utilized for multimedia information support. Decisionarium also offers access to complete e‐learning modules ( www.dm.hut.fi ) based on the use of the software. There are also illustrative powerpoint presentations and additional Windows software WINPRE and PRIME‐Decisions for value tree analysis under incomplete information. Copyright © 2004 John Wiley & Sons, Ltd.     

Group‐analytic network process for balancing stakeholder views on fire protection of steel‐framed buildings

To select appropriate fire protection options for buildings during their design stage, economic, safety, environmental, and societal criteria need to be accounted for. The divergent and sometimes conflictual desires from different fire design stakeholders involved in the process present a multicriteria decision problem. Design decision criteria and fire protection options can be interdependent, and so there is a need to manage these desires with an advanced decision analysis technique, thereby reducing uncertainties in the complex decision‐making process. The aim of this paper is to use the weighted/geometric mean method‐analytic network process (W/GMM‐ANP) to balance the opinions of fire design stakeholders extracted from 42 structured stakeholder interviews on selecting the most suitable fire protection option for buildings constructed of steel frames. Different categories of interdependent decision elements were developed from 22 design decision criteria and 5 proposed fire protection options to produce a network of decision clusters for multicriteria decision analysis. In the synthesis and ranking of fire protection options, the W/GMM‐ANP accounted for the multiple interdependencies of weighted and unweighted stakeholder desires and managed the complexity of the decision‐making problem. The technique is proposed for approaching suitable group decisions in structural fire design of steel‐framed buildings as well as other performance‐based engineering decision making that may involve multidisciplinary stakeholders.     

Procedural fairness in ultimatum bargaining: Effects of interactional fairness and formal procedure on respondents’ reactions to unequal offers1

Abstract: Ninety‐nine Japanese students received one of three offers in an ultimatum bargaining scenario: unfavorable and unequal; equal; or favorable but unequal. These offers were determined by either the other participant or by a computerized lottery. We also manipulated the arbitrariness of the role assignment procedure. Participants perceived the intentional small offer as more unfair in the interactional sense than the unintentional small offer, while they perceived the same offers as unfair in the distributive sense, regardless of intentionality. The intentional small offer was more likely to be rejected than the unintentional small offer. Participants perceived the arbitrary procedure of the role assignment as highly unfair, whereas the difference of arbitrariness in role assignment procedures had no significant impact on their reactions to the offer. Acceptance of the offer was strongly determined by interactional fairness, as well as by distributive fairness, and these types of fairness were influenced by different situational characteristics, such as intentionality, the size of the offer, and the equality of the offer.     

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.     

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.