Group decision making based on intuitionistic multiplicative aggregation operators

Preference relations are the most common techniques to express decision maker’s preference information over alternatives or criteria. To consistent with the law of diminishing marginal utility, we use the asymmetrical scale instead of the symmetrical one to express the information in intuitionistic fuzzy preference relations, and introduce a new kind of preference relation called the intuitionistic multiplicative preference relation, which contains two parts of information describing the intensity degrees that an alternative is or not priority to another. Some basic operations are introduced, based on which, an aggregation principle is proposed to aggregate the intuitionistic multiplicative preference information, the desirable properties and special cases are further discussed. Choquet Integral and power average are also applied to the aggregation principle to produce the aggregation operators to reflect the correlations of the intuitionistic multiplicative preference information. Finally, a method is given to deal with the group decision making based on intuitionistic multiplicative preference relations.     

Empirical properties of group preference aggregation methods employed in AHP: Theory and evidence

We study various methods of aggregating individual judgments and individual priorities in group decision making with the AHP. The focus is on the empirical properties of the various methods, mainly on the extent to which the various aggregation methods represent an accurate approximation of the priority vector of interest. We identify five main classes of aggregation procedures which provide identical or very similar empirical expressions for the vectors of interest. We also propose a method to decompose in the AHP response matrix distortions due to random errors and perturbations caused by cognitive biases predicted by the mathematical psychology literature. We test the decomposition with experimental data and find that perturbations in group decision making caused by cognitive distortions are more important than those caused by random errors. We propose methods to correct the systematic distortions.     

A goal programming approach to group decision making based on multiplicative preference relations and fuzzy preference relations

This paper analyses the mechanisms through which binding finance constraints can induce debt-constrained firms to improve technical efficiency to guarantee positive profits. This hypothesis is tested on a sample of firms belonging to the Italian manufacturing. Technical efficiency scores are computed by estimating parametric production frontiers using the one stage approach as in Battese and Coelli [Battese, G., Coelli, T., 1995. A model for technical efficiency effects in a stochastic frontier production function for panel data. Empirical Economics 20, 325–332]. The results support the hypothesis that a restriction in the availability of financial resources can affect positively efficiency.     

An approach to group decision making based on interval multiplicative and fuzzy preference relations by using projection

This paper presents a consensus model for group decision making with interval multiplicative and fuzzy preference relations based on two consensus criteria: (1) a consensus measure which indicates the agreement between experts’ preference relations and (2) a measure of proximity to find out how far the individual opinions are from the group opinion. These measures are calculated by using the relative projections of individual preference relations on the collective one, which are obtained by extending the relative projection of vectors. First, the weights of experts are determined by the relative projections of individual preference relations on the initial collective one. Then using the weights of experts, all individual preference relations are aggregated into a collective one. The consensus and proximity measures are calculated by using the relative projections of experts’ preference relations respectively. The consensus measure is used to guide the consensus process until the collective solution is achieved. The proximity measure is used to guide the discussion phase of consensus reaching process. In such a way, an iterative algorithm is designed to guide the experts in the consensus reaching process. Finally the expected value preference relations are defined to transform the interval collective preference relation to a crisp one and the weights of alternatives are obtained from the expected value preference relations. Two numerical examples are given to illustrate the models and approaches.     

A goal programming model for incomplete interval multiplicative preference relations and its application in group decision-making

In decision making problems, there may be the cases where the decision makers express their judgements by using preference relations with incomplete information. Then one of the key issues is how to estimate the missing preference values. In this paper, we introduce an incomplete interval multiplicative preference relation and give the definitions of consistent and acceptable incomplete ones, respectively. Based on the consistency property of interval multiplicative preference relations, a goal programming model is proposed to complement the acceptable incomplete one. A new algorithm of obtaining the priority vector from incomplete interval multiplicative preference relations is given. The goal programming model is further applied to group decision-making (GDM) where the experts evaluate their preferences as acceptable incomplete interval multiplicative preference relations. An interval weighted geometric averaging (IWGA) operator is proposed to aggregate individual preference relations into a social one. Furthermore, the social interval multiplicative preference relation owns acceptable consistency when every individual one is acceptably consistent. Two numerical examples are carried out to show the efficiency of the proposed goal programming model and the algorithms.     

Fuzzy preference orderings in group decision making

In this paper, some use of fuzzy preference orderings in group decision making is discussed. First, fuzzy preference orderings are defined as fuzzy binary relations satisfying reciprocity and max-min transitivity. Then, particularly in the case where individual preferences are represented by utility functions (utility values), group fuzzy preference orderings of which fuzziness is caused by differences or diversity of individual opinions are defined. Those orderings might be useful for proceeding the group decision making process smoothly, in the same manner as the extended contributive rule method.     

Pareto optimality and robustness in bi-blending problems

The mixture design problem for two products concerns finding simultaneously two recipes of a blending problem with linear, quadratic and semi-continuity constraints. A solution of the blending problem minimizes a linear cost objective and an integer valued objective that keeps track of the number of raw materials that are used by the two recipes, i.e. this is a bi-objective problem. Additionally, the solution must be robust. We focus on possible solution approaches that provide a guarantee to solve bi-blending problems with a certain accuracy, where two products are using (partly) the same scarce raw materials. The bi-blending problem is described, and a search strategy based on Branch-and-Bound is analysed. Specific tests are developed for the bi-blending aspect of the problem. The whole is illustrated numerically.     

MCDA and preference disaggregation in group decision support systems

Within the frame of decision aid literature, group decision making has drawn the attention of researchers from a wide spectrum of disciplines. Group Decision Support Systems (GDSS) can play a critical role, in decision situations with multiple individuals, each having his/her own private point of view on the handling of the decision problem. In such an environment, the conflict between the members of the group is not a seldom situation. Multiple criteria decision aid (MCDA) methods can be proven as invaluable tools in handling such interpersonal conflicts where the aim is to achieve consensus between the group members or at least reduce the amount of conflict among participating individuals. This paper reviews some of the past approaches in the multiple criteria–multiple decision makers context.     

Group algebras of periodic groups of a solvable multiplicative group

The structure of the group algebra KG of an arbitrary periodic group G such that the multiplicative group U(KG) is solvable is completely determined. Translated from Matematicheskie Zametki, Vol. 22, No. 3, pp. 421–432, September, 1977.     

Neural nets in a group decision process

In recent years there has been some interest in applying Artificial Adaptive Agents (AAA) to the study of complex adaptive systems, especially economic systems. Neural networks are frequently employed as AAA. Artificial neural nets mimic certain aspects of the physical structure and information processing of the human brain and their most attractive characteristic is their ability to learn a pattern from a given set of examples. In this study, we investigated the ability of neural nets to model human behavior in a group decision process. The context was a market entry game with a linear payoff function and binary decisions. The players had to decide, for each trial, whether or not to enter a market whose capacity is public knowledge. Human behavior in this situation has been modeled and empirically validated by the Nash equilibrium for noncooperative n-person games. A simulation of the game was performed with neural nets instead of human subjects. The nets were trained using the results of the games in which they participated. The simulation with groups of neural nets exhibits phenomena very similar to those observed in groups of human players. Received February 2000     

Pareto optimality and a class of set covering heuristics

The set covering problem has many diverse applications to problems arising in crew scheduling, facility location and other business areas. Since the problem is known to be hard to solve optimally, a number of approximate (heuristic) approaches have been designed for it. These approaches (with one exception) divide into two main groups, greedy heuristics and dual saturation heuristics. We use the concept of a Pareto optimal dual solution to show that an arbitrary dual saturation heuristic has the same worst-case performance guarantee as the two best known heuristics of that type. Moreover, this poor performance level is always attainable by those two heuristics.     

A decision process over variables and their number: Two-phase optimality conditions

The paper considers the following unconstrained optimization problem: minimize f_n(x_n, n) = g_n(x_n) + h(n), where g_n(x_n) = α?_{i = 0}^n?1 ∫ _xi^{x_i = 1} [ ∫ _x^{x_i + 1}b (t) d(t)]d x, over both the variables x₁, x₂, …, x_n?1, and their number n, when x₀, x_n ≡ X are known boundary conditions, and h (n) is increasing, unbounded and weakly convex. Examples that demonstrate the practical usefulness of this decision process are given, and a two-phase approach for solving it, namely, minimize first over the arguments for a fixed n, and then over n, is suggested. Simple conditions, for a general g_n(x_n), under which phase II can be carried out by a finite search are stated, and then the question: “Under what circumstances does the search for the optimal n reduce to a simple condition?” is posed. Kuhn-Tucker type two-phase optimality conditions that answer this question are established, and moreover, specifications on the dominating single variable function b (x) for which the conditions hold are set forth.     

Pareto optimality,anonymity, and strategy-proofness in location problems

Generalized location problems withn agents are considered, who each report a point inm-dimensional Euclidean space. A solution assigns a compromise point to thesen points, and the individual utilities for this compromise point are equal to the negatives of the Euclidean distances to the individual positions. Form = 2 andn odd, it is shown that a solution is Pareto optimal, anonymous, and strategy-proof if, and only if, it is obtained by taking the coordinatewise median with respect to a pair of orthogonal axes. Further, for all other situations withm2, such a solution does not exist. A few results concerning other solution properties, as well as different utility functions, are discussed.Supported by a grant from the Cooperation Centre Tilburg and Eindhoven University.     

On Pareto optimality conditions in the case of two-dimension non-convex utility space

The paper suggests a new — to the best of the author’s knowledge — characterization of Pareto-optimal decisions for the case of two-dimensional utility space which is not supposed to be convex. The main idea is to use the angle distances between the bisector of the first quadrant and points of utility space. A necessary and sufficient condition for Pareto optimality in the form of an equation is derived. The first-order necessary condition for optimality in the form of a pair of equations is also obtained.     

Nilpotency of the multiplicative group of a group ring

It is proven that if K is a commutative ring of characteristic p^m while group G contains p-elements, then the multiplicative group UKG of group ring KG is nilpotent if and only if G is nilpotent and its commutant G is a finite p-group. Those group algebras KG are described for which the nilpotency classes of groups G and UKG coincide.Translated from Matematicheskie Zametki, Vol. 11, No. 2, pp. 191–200, February, 1972.In conclusion, the author wishes to express her gratitude to A. A. Bovdi for his scientific direction.     

Group decision making with expertons and uncertain generalized probabilistic weighted aggregation operators

Expertons and uncertain aggregation operators are tools for dealing with imprecise information that can be assessed with interval numbers. This paper introduces the uncertain generalized probabilistic weighted averaging (UGPWA) operator. It is an aggregation operator that unifies the probability and the weighted average in the same formulation considering the degree of importance that each concept has in the aggregation. Moreover, it is able to assess uncertain environments that cannot be assessed with exact numbers but it is possible to use interval numbers. Thus, we can analyze imprecise information considering the minimum and the maximum result that may occur. Further extensions to this approach are presented including the quasi-arithmetic uncertain probabilistic weighted averaging operator and the uncertain generalized probabilistic weighted moving average. We analyze the applicability of this new approach in a group decision making problem by using the theory of expertons in strategic management.     

On cone characterizations of weak, proper and Pareto optimality in multiobjective optimization

Efficient, weakly and properly Pareto optimal solutions of multiobjective optimization problems can be characterized with the help of different cones. Here, contingent, tangent and normal cones as well as cones of feasible directions are used in the characterizations. The results are first presented in convex cases and then generalized to nonconvex cases by employing local concepts.     

Generalized nilpotency of the multiplicative group of a group ring

Translated from Ukrainskii Matematicheskii Zhurnal, Vol. 41, No. 9, pp. 1179–1183, September, 1989.