Multiple criteria decision making with interactive over-achievement programming

Whereas in goal programming the under-achievement with respect to (usually) unattainable goals are minimized, we propose the maximization of the over-achievements with respect to feasible goals or required values. An interactive algorithm, in which the over-achievements are maximized via a barrier function, is presented to implement the proposed approach.     

Preference relations on actions and criteria in multicriteria decision making

Let A be a finite set of feasible actions which are judged following several criteria. An outranking relation is defined on A by considering preference of the decision maker as a weak order on each criterion and the relation among criteria as a semi-order on the given set of criteria.Several ways of constructing outranking relations have been proposed. One of the most popular, introduced by B. Roy, for instance ELECTRE(s), is based on the use of weights related to criteria. In our approach, the knowledge of weights is replaced by the existence of a semi-order.A case study is developed. It deals with a computer selection problem.     

Multiple criteria decision making combined with finance: A categorized bibliographic study

This paper provides a categorized bibliography on the application of the techniques of multiple criteria decision making (MCDM) to problems and issues in finance. A total of 265 references have been compiled and classified according to the methodological approaches of goal programming, multiple objective programming, the analytic hierarchy process, etc., and to the application areas of capital budgeting, working capital management, portfolio analysis, etc. The bibliography provides an overview of the literature on “MCDM combined with finance,” shows how contributions to the area have come from all over the world, facilitates access to the entirety of this heretofore fragmented literature, and underscores the often multiple criterion nature of many problems in finance.     

Planning federal public investment in Mexico using multiobjective decision making

The scope of this article is showing how multicriteria decision making can be anefficient tool to manage public investment planning in complex situations. Forthis aim, we will analyse the problem in all its aspects: building the modelfrom data using econometrical tools, solving the resulting highly complex modelusing modern efficient techniques (multiobjective meta-heuristics) and helpingthe decision maker to introduce his preferences in order to achieve the mostpreferred solution. This holistic approach let us provide an efficient solutionto a complex public investment planning situation, improving the current stateof the country relating not only economical aspects, but also social and humandevelopment aspects. The real situation studied is focused on Mexico, where, inrecent decades, has undergone remarkable improvements in terms of economicgrowth, which has not been matched by significant improvements in several otherbasic aspects of human development, nor by reductions in regional inequalities.This suggests the need to establish policies aimed at improving these aspectsand reducing inequalities. Federal public investment is an important tool inregional policy to promote and improve these aspects; so we introduce amultiobjective programming problem for planning federal public investment inMexico. This model will focus on improving national levels in four maindimensions of human development (economic growth, education, health andhousing), and on reducing regional inequalities for those dimensions.     

Complete intersections and rational equivalence

A new criterion for rational equivalence of cycles on a projective variety over an algebraically closed field is given, and some consequences considered.     

Regularized estimation for preference disaggregation in multiple criteria decision making

Disaggregation methods have been extensively used in multiple criteria decision making to infer preferential information from reference examples, using linear programming techniques. This paper proposes simple extensions of existing formulations, based on the concept of regularization which has been introduced within the context of the statistical learning theory. The properties of the resulting new formulations are analyzed for both ranking and classification problems and experimental results are presented demonstrating the improved performance of the proposed formulations over the ones traditionally used in preference disaggregation analysis.     

An action learning evaluation procedure for multiple criteria decision making problems

In this paper we focus on an extension of the Analytic Hierarchy Process (AHP) that accommodates ambiguity on the part of the decision maker (DM), and facilitates the exploration of the decision domain. We propose a systematic action learning process that builds confidence as it converges from numeric interval estimates to numeric point estimates. Our Multiple Criteria Decision Making (MCDM) problem procedure structures the problem as a hierarchy, evaluates all objects using pairwise comparisons that accommodate vagueness and ambiguity, uses interval prioritization techniques, and does synthesis using the linear additive value function. This action learning process facilitates the understanding of key stakeholders, which is imperative for the successful implementation of the subsequent decision.     

Using interdependent information on the relative importance of criteria in decision making

A multicriteria choice problem is considered. The Edgeworth-Pareto principle is established under the assumption that certain axioms hold true. Quantitative interdependent information on the relative importance of two groups of criteria is used to derive upper bounds for the unknown set of selected vectors.     

Revising the OWA operator for multi criteria decision making problems under uncertainty

Multi criteria decision making (MCDM) problems are usually under uncertainty. One of these uncertain parameters is the decision maker (DM)’s degree of optimism, which has an important effect on the results. Fuzzy linguistic quantifiers are used to obtain the assessments of this parameter from DM and then, because of its uncertainty it is assumed to have stochastic nature. A new approach, entitled FSROWA, is introduced to combine the Fuzzy and Stochastic features into a Revised OWA operator.     

An integrated multiple criteria decision making model applying axiomatic fuzzy set theory

This article presents a hybrid model for the multiple criteria decision making problems. The proposed decision model consists of three parts: (i) DEA (data envelopment analysis) is used to provide the best combination on the performance parameters of original data; (ii) By the application of AFS (axiomatic fuzzy set) theory and AHP (analytic hierarchy process) method, the weight of each attribute is calculated and (iii) TOPSIS (technique for order preference by similarity to ideal solution) is applied to provide the ranking order of that best combination based on the weights of attributes. In addition, we also provide the definitely semantic interpretations for the decision results by AFS theory. Specially, the model not only employs the performance parameters from raw data, but also considers the preferences from decision-makers that can make the decision results more reasonable. The proposed model is used for robot selection to verify the proposed model. Using the selection index, the evaluation of alternative robots and the selection of the most appropriate are eventually feasible. Moreover, a numerical example for supplier selection is included to illustrate the application of the model for the newly developed problems.     

Dynamic multiple criteria decision making in changeable spaces: from habitual domains to innovation dynamics

Human behaviors involve dynamic, evolving, interactive and adaptive processes. Important decision makings usually are dynamic, involving multiple criteria in changeable spaces. This article introduces the behavior mechanism that integrates the findings of neural science, psychology, system science, optimization theory and multiple criteria decision making. It shows how our brain and mind operate and describes our behaviors and decision making as dynamic processes of multiple criteria decision making in changeable spaces. Unless extraordinary events occur or special effort exerted, the dynamic processes will be stabilized in certain domains, known as Habitual Domains. Habitual Domains, which play a vital role in upgrading the quality of our decision making and lives, will be explored. In addition, as important consequential derivatives, concepts of Competence Set Analysis and Innovation Dynamics will also be discussed. Note that these concepts involve transitions between dynamic and static states.     

Conditional identity calculus and conditioned rational equivalence

We construct a conditional identity calculus (similar to the Birkhoff identity calculus), which complies with the concept of truth for a conditional identity on a universal algebra. The relationship is studied between the isomorphism of embedding categories of conditional varieties and the conditioned rational equivalence of these varieties. As applications, we describe invariants for the relations ‘is conditional rational equivalent’ and ‘is similar’ on finite universal algebras. Supported by RFFR grant No. 93-01-01520. Translated fromAlgebra i Logika, Vol. 37, No. 4, pp. 432–459, July–August, 1998.     

A visual interactive approach for multiple criteria decision making with monotone utility functions

We consider the problem of choosing the best of a set of alternatives where each alternative is evaluated on multiple criteria. We develop a visual interactive approach assuming that the decision maker (DM) has a general monotone utility function. The approach partitions the criteria space into nonoverlapping cells. The DM uses various graphical aids to move between cells and to further manipulate selected cells with the goal of creating cells that have ideal points less preferred than an alternative. When the DM identifies such cells, all alternatives in those cells are eliminated from further consideration. The DM may also compare pairs of alternatives. The approach terminates with the most preferred alternative of the DM.     

A multiple criteria decision making approach to manure management systems in the Netherlands

The intensification of livestock operations in the last few decades has resulted in an increased social concern over the environmental impacts of livestock operations and thus making appropriate manure management decisions increasingly important. A socially acceptable manure management system that simultaneously achieves the pressing environmental objectives while balancing the socio-economic welfare of farmers and society at large is needed. Manure management decisions involve a number of decision makers with different and conflicting views of what is acceptable in the context of sustainable development. This paper developed a decision-making tool based on a multiple criteria decision making (MCDM) approach to address the manure management problems in the Netherlands. This paper has demonstrated the application of compromise programming and goal programming to evaluate key trade-offs between socio-economic benefits and environmental sustainability of manure management systems while taking decision makers’ conflicting views of the different criteria into account. The proposed methodology is a useful tool in assisting decision makers and policy makers in designing policies that enhance the introduction of economically, socially and environmentally sustainable manure management systems.     

A multiple criteria decision making approach for electricity planning in Spain: economic versus environmental objectives

Growing social concern about the environmental impact of economic development has drawn attention to the need to integrate environmental criteria into energy decision-making problems. This has made electricity planning issues more complex given the multiplicity of objectives and decision-makers involved in the decision making process. This paper proposes a methodology that combines several multi-criteria methods to address electricity planning problems within a realistic context. The method is applied to an electricity planning exercise in Spain with a planning horizon set for the year 2030. The model includes the following objectives: (1) total cost; (2) C0₂; (3) SO₂; and (4) NO _x emissions as well as the amount of radioactive waste produced. An efficient social compromise between these conflicting objectives is obtained, which shows the advantages of using this model for policy-making purposes.     

A new decision support model in multi-criteria decision making with intuitionistic fuzzy sets based on risk preferences and criteria reduction

In this paper, we propose a new model for decision support to address the ‘large decision table’ (eg, many criteria) challenge in intuitionistic fuzzy sets (IFSs) multi-criteria decision-making (MCDM) problems. This new model involves risk preferences of decision makers (DMs) based on the prospect theory and criteria reduction. First, we build three relationship models based on different types of DMs’ risk preferences. By building different discernibility matrices according to relationship models, we find useful criteria for IFS MCDM problems. Second, we propose a technique to obtain weights through discernibility matrix. Third, we also propose a new method to rank and select the most desirable choice(s) according to weighted combinatorial advantage values of alternatives. Finally, we use a realistic voting example to demonstrate the practicality and effectiveness of the proposed method and construct a new decision support model for IFS MCDM problems.     

The impact of investment lags on investment decision

This paper suggests a valuation framework for an investment project through the concept of real options. Generally, in real asset world, decision time and its payment time are not identical. This so-called investment lag problem should be considered when valuing real assets. When investment lags exist, firms’ accommodation capacities play important roles. In this paper, the real effect of investment lag on investment value is tested upon various conditions. We show the valuation process of real assets under the risk-neutral world. The closed-form formula is also provided for valuing real assets, including R&D project.