决策者具有(严格)凸性偏好结构下的一类交互式多目标决策方法

为了更好地解决决策者具有(严格)凸性偏好结构下的多目标决策问题,一般目标空间为有界凸域的情形常常可以转化为目标空间为有界闭凸区域的情形,首先分析了切割平面及该平面上偏好最优点与被切割平面分割成的为有界闭凸区域的目标空间或目标空间的子集的两个部分之间的关系;然后分析并指出了对于包含全局偏好最优目标方案点的为有界闭凸域的目标空间及其子集(准最优目标集),在确定了切割平面上的偏好最优点后,通过适当地选取供决策者与切割平面的偏好最优点进行比较判断的目标方案点,经过一次比较就可以确定一个新的范围更小的包含全局偏好最优目标方案点的目标空间的有界闭凸子区域(准最优目标集).为获取切割平面上的偏好最优点,提出了改进的坐标轮换法.在这些结论和方法的基础上,提出了决策者具有(严格)凸性偏好结构下的一类交互式多目标决策方法,要求决策者提供较易的偏好性息,决策效能较好.     

区间型多属性群体专家权重的确定方法

针对方案偏好和属性值均为区间数的多属性群决策问题，研究了群体专家权重的确定，并提出了一种新的群决策方法．通过定义区间数向量的内积，计算专家评判的相似度和差异度，进而客观地确定了专家的权重．求解最小化主、客观偏差的目标规划模型，得到了属性的权重，利用方案的群体综合属性值给出排序结果．供应商选择的应用实例验证了方法的可行性和合理性．     

线路方案比选多目标决策分析

本文通过对线路方案比选的多目标决策分析，建立了线路方案比选的 ＴＯＰＳＩＳ模型，对线路方案非劣解集进行排序，提供方案的优先顺序．     

A fuzzy-stochastic OWA model for robust multi-criteria decision making

All realistic Multi-Criteria Decision Making (MCDM) problems face various kinds of uncertainty. Since the evaluations of alternatives with respect to the criteria are uncertain they will be assumed to have stochastic nature. To obtain the uncertain optimism degree of the decision maker fuzzy linguistic quantifiers will be used. Then a new approach for fuzzy-stochastic modeling of MCDM problems will be introduced by merging the stochastic and fuzzy approaches into the OWA operator. The results of the new approach, entitled FSOWA, give the expected value and the variance of the combined goodness measure for each alternative. Robust decision depends on the combined goodness measures of alternatives and also on the variations of these measures under uncertainty. In order to combine these two characteristics a composite goodness measure will be defined. The theoretical results will be illustrated in a watershed management problem. By using this measure will give more sensitive decisions to the stakeholders whose optimism degrees are different than that of the decision maker. FSOWA can be used for robust decision making on the competitive alternatives under uncertainty.     

Resolution approach for multi-objective problems with uncertain demands

The job-shop scheduling problem (JSP) is one of the hardest problems (NP-complete problem). In a lot of cases, the combination of goals and resource exponentially increases search space. The objective of resolution of such a problem is generally, to maximize the production with a lower cost and makespan. In this paper, we explain how to modify the objective function of genetic algorithms to treat the multi-objective problem and to generate a set of diversified “optimal” solutions in order to help decision maker. We are interested in one of the problems occurring in the production workshops where the list of demands is split into firm (certain) jobs and predicted jobs. One wishes to maximize the produced quantity, while minimizing as well as possible the makespan and the production costs. Genetic algorithms are used to find the scheduling solution of the firm jobs because they are well adapted to the treatment of the multi-objective optimization problems. The predicted jobs will be inserted in the real solutions (given by genetic algorithms). The solutions proposed by our approach are compared to the lower bound of the cost and makespan in order to prove the quality and robustness of our proposed approach.     

A fuzzy simple additive weighting system under group decision-making for facility location selection with objective/subjective attributes

This work presents a new fuzzy multiple attributes decision-making (FMADM) approach, i.e., fuzzy simple additive weighting system (FSAWS), for solving facility location selection problems by using objective/subjective attributes under group decision-making (GDM) conditions. The proposed system integrates fuzzy set theory (FST), the factor rating system (FRS) and simple additive weighting (SAW) to evaluate facility locations alternatives. The FSAWS is applied to deal with both qualitative and quantitative dimensions. The FSAWS process considers the importance of each decision-maker, and the total scores for alternative locations are then derived by homo/heterogeneous group of decision-makers. Finally, a numerical example illustrates the procedure of the proposed FSAWS.     

群体决策随机偏爱数映射的若干性质

1引言近年来,群体决策在社会选择、福利、经济和军事等领域得到广泛应用,从而其理论研究越来越被人们所重视.20世纪中叶,K.J,Arrow提出了偏爱公理系和不可能性定理,并     

目标属性为肯定和否定的多目标决策问题解的有效性条件

本文建立了一类目标属性为肯定和否定的多目标决策模型，定义了相应的有效性。并在此基础上，讨论了有效性条件。     

一致性互反Fuzzy判断矩阵的传递性

研究矩阵元素为Fuzzy数的互反判断矩阵的传递性质.首先得到了判断两个Fuzzy数近似相等的等价条件,并得到了揭示Fuzzy数的核之间关系的一个充要条件.在此基础上,进一步证明了一致性互反Fuzzy判断矩阵具有传递性的两个结论.这两个结论说明:在层次分析法中,用一致性互反Fuzzy判断矩阵表示一组方案在同一目标下的两两重要性比较是符合理性决策的思维特征的.     

An algorithm for ordinal sorting based on ELECTRE with categories defined by examples

This work proposes a Progressive Assisted Sorting Algorithm (PASA) based on a multicriteria evaluation ELECTRE-type method. The purpose of the PASA is to aid a decision maker to progressively sort a set of alternatives into a set of categories, which we considered are ordered (ordinal sorting), following a consistency principle. We consider the principle that if an alternative outranks (is as good as) a second one, then it must belong to the same category or to a better category. The set of alternatives already sorted by the decision maker will implicitly define the categories, and will constrain the range of categories where other alternatives may be sorted. We show how the same idea may be used in an aggregation/disaggregation approach, considering some parameters of ELECTRE are not fixed a priori, but are constrained only by the examples provided. In this context, we establish a “convex-shape property” stating that the range of possible categories for an alternative is always an interval of categories. A discussion contrasting this approach with ELECTRE TRI is included in the conclusions.