Multicriteria Goal Games

In this paper, we deal with multicriteria matrix games. Different solution concepts have been proposed to cope with these games. Recently, the concept of Pareto-optimal security strategy which assures the property of security in the individual criteria against an opponent's deviation in strategy has been introduced. However, the idea of security behind this concept is based on expected values, so that this security might be violated by mixed strategies when replications are not allowed. To avoid this inconvenience, we propose in this paper a new concept of solution for these games: the G-goal security strategy, which includes as part of the solution the probability of obtaining prespecified values in the payoff functions. Thus, attitude toward risk together with payoff values are considered jointly in the solution analysis.     

Fuzzy Multi-fractional Programming for Land Use Planning in Agricultural Production System

In this paper, we present a multi-objective linear fractional programming (MOLFP) approach for multi-objective linear fuzzy goal programming (MOLFGP) problem. Here, we consider a problem in which a set of pair of goals are optimized in ratio rather than optimizing them individually. In particular, we consider the optimization of profit to cash expenditure and crop production in various seasons to land utilization as a fractional objectives and used remaining goals in its original form. Further, the goals set in agricultural production planning are conflicting in nature; thus we use the concept of conflict and nonconflict between goals for computation of appropriate aspiration level. The method is illustrated on a problem of agricultural production system for comparison with Biswas and Pal [1] method to show its suitability.     

Novice facilitators’ changes in practices: From launching to managing discussions about mathematics teaching

Novice facilitators of professional development (PD) programs for mathematics teachers often face challenges in leading productive discussions and achieving the goals of these programs. Although research in this area is gradually accumulating, not much is known about how novice facilitators address these challenges and change their practices accordingly. This paper presents case studies of two novice facilitators of PD programs in two different countries. The analyses look at their work over one year, to illustrate the changes in their practices while managing discussions. The results show that although the facilitators operated in different contexts, their practices and their processes of change resembled, suggesting that these processes are not idiosyncratic. We argue that novice facilitators’ changes in practices correspond to changes in their resources, orientations, goals, and identities and that PD program teams can support these changes.     

Making use of social prototypes: From fuzzy concepts to firm decisions

Evidence suggestive of the ‘fuzzy’ structure of many natural language (as opposed to scientific) categories is reviewed. Examples are drawn from categorization schemes for objects, such as cars, fruit or tables, as well as for people, such as extroverts, hippies and ‘fraternity types’. It is argued that despite the fuzziness of natural categories, there is orderliness and utility to these concepts, as well. Specifically, natural categories are organized around prototypes, representative category members, which serve as reference points for the category. The identification of category members involves a prototype-matching process. Prototypes about ‘kinds of people’ can be very useful in decisions about people with whom to affiliate and places in which to live. This process was illustrated by reference to a case analysis of students' preferences for university housing. It was concluded that natural categories may well be fuzzy, but they are far from being dispensible.     

On-Line Constrained Predictive Control Algorithm using Multi-Objective Fuzzy-Optimization and a Case Study

Model predictive control (MPC) has been used in process control systems with constraints, however, the constrained optimization problem involved in control systems has generally been solved in practice in a piece-meal fashion. To solve the problem systemically, in this paper, the Multi-Objective Fuzzy-Optimization (MOFO) is used in the constrained predictive control for online applications as a means of dealing with fuzzy goals and fuzzy constraints in control systems. The conventional model predictive control is integrated with the techniques from fuzzy multicriteria decision making, translating the goals and the constraints to predictive control in a transparent way. The information regarding the fuzzy goals and the fuzzy constraints of the control problem is combined by using a decision function from the fuzzy theory, so it is possible to aggregate the fuzzy goals and the fuzzy constraints using fuzzy operators, e.g. t-norms, s-norms or the convex sum. It is shown that the model predictive controller based on MOFO allows the designers a more flexible aggregation of the control objectives than the usual weighting sum of squared errors in MPC. The efficiency of the presented algorithm is validated by the visual robot path planning.     

Fuzzy matrix games via a fuzzy relation approach

A generalized model for a two person zero sum matrix game with fuzzy goals and fuzzy payoffs via fuzzy relation approach is introduced, and it is shown to be equivalent to two semi-infinite optimization problems. Further, in certain special cases, it is observed that the two semi-infinite optimization problems reduce to (finite) linear programming problems which are dual to each other either in the fuzzy sense or in the crisp sense.     

具有模糊目标的多目标双矩阵对策集结与求解

针对不确定性多冲突环境,建立了多个具有模糊目标的多目标双矩阵对策的综合集结模型.在假定局中人各模糊目标的隶属函数为线性函数的情形下,基于总体模糊目标的可达度,给出了纳什均衡解的定义,并应用粒子群优化算法对集结模型求解.最后,给出一个军事例子说明了模型的实用有效性和粒子群优化算法求解的高效性.     

Measuring overall efficiency and effectiveness using DEA

This paper presents a framework where data envelopment analysis (DEA) is used to measure overall efficiency and show how to apply this framework to assess effectiveness for more general behavioral goals. The relationships between various cone-ratio DEA models and models to measure overall efficiency are clarified. Specifically it is shown that as multiplier cones tighten, the cone-ratio DEA models converge to measures of overall efficiency. Furthermore, it is argued that multiplier cone and cone-ratio model selection must be consistent with the behavioral goals assigned or assumed for purposes of analysis. Consistent with this reasoning, two new models are introduced to measure effectiveness when value measures are represented by separable or linked cones, where the latter can be used to analyze profit-maximizing effectiveness.     

Collective stochastic versions of playable games as metaphors for complex biosystems: Team connect four

In an effort to better understand complex biological systems, the game “Connect Four” is generalized to be a stochastic contest between two teams. Members of each team typically possess “sensors” that provide some information on the nearby deployment of the pieces. Sensing something interesting increases the probability that a given team member will move. Simulations show the relative strengths of various sensor weightings and thereby cast some light on the use of sensors in more general complex autonomous systems. © 2003 Wiley Periodicals, Inc.     

Quality control system design through the goal programming model and the satisfaction functions

The goal programming (GP) model has been utilized for designing a quality control system (QCS) where several features are simultaneously considered. In the context of the quality control, the parameters can be imprecise and expressed through intervals. The aim of this paper is to propose two formulations for designing a QCS based on the imprecise GP model. The concept of satisfaction functions will be utilized to integrate explicitly the decision-maker’s preference. The developed formulations are illustrated through an example of a paper factory.