Approximations and Well-Posedness in Multicriteria Games

First, sufficient conditions of minimal character are given which guarantee the sequential closedness of the set-valued function defined by the parametric weak-multicriteria Nash equilibria of a parametric multicriteria game, that is to say: a convergent sequence of parametric weak-multicriteria Nash equilibria, corresponding to an approximate value of the parameter x_n, converges to a weak-multicriteria Nash equilibrium corresponding to the limit value x of the sequence (x_n)_n. Then, approximating sequences and parametrically well-posedness for a multicriteria game are introduced and investigated.     

A multiclass,multicriteria logit-based traffic equilibrium assignment model under ATIS

This paper presents a multiclass, multicriteria (cost versus time) logit-based traffic equilibrium assignment model in road networks served by advanced traveler information systems (ATIS). All users are differentiated by their own value of time (VOT) that follows some probability distribution. Users of each class, having their own VOT, are further divided into two groups, equipped and unequipped with ATIS respectively. The travel disutility received by each user is defined as a linear bi-criteria combination of travel time and monetary travel cost. It is assumed that all users make their route choices in a logit-based stochastic manner, but the equipped users have lower perception variation on the travel disutility than the unequipped due to the ATIS service. The model is formulated as a fixed-point problem and solved by the method of successive averages in conjunction with logit assignment. Numerical results show that the traditional single-class and/or single-criterion models may overestimate or underestimate the benefit from ATIS services.     

Some advantages of stochastic methods in multicriteria optimization of multibody systems

Summary Optimization methods became an important tool for the synthesis of complex mechanical systems. However, while deterministic approaches usually yield good convergence within a few iterations, they often lead to local minima only. Stochastic optimization, like simulated annealing, is not as sensitive with respect to local minima, but often requires high computational effort. In this paper, we describe an optimization concept founded on either a deterministic gradient-based method or a stochastic simulated annealing optimization procedure. An application to vehicle dynamics and a comparison of the different procedures is given. It turns out that simulated annealing does not only avoid local minima, but also helps to give a clearer picture of the Edgeworth-Pareto optimal set and improves the judgement of the influence of nonsensitive parameters. Beside efficiency, these properties also have to be considered when it is decided whether a stochastic or a deterministic optimization algorithm should be chosen. Received 19 April 1999; accepted for publication 8 May 1999     

权重信息未知对方案有偏好的vague集多指标决策

就指标权重未知,且对方案有偏好的vague集多指标决策问题,提出了通过使决策者的主观偏好值与属性值的相离度最小来建立最优化模型,从而获得指标的权重.通过将vague值转化为模糊值来建立模糊值矩阵,由模糊值矩阵按各指标对应值的大小对方案进行排序,形成多个线性序,进而由线性序来构造模糊优先矩阵,对其进行截割,得到最优方案.最后通过一个实例说明此方法的具体决策过程.     

最小化加权误工工件数的多代理平行分批排序

考虑多代理的平行分批排序,不同代理的工件不能放在同一批中加工,目标函数是最小化加权误工工件数.本文考虑两种模型,证明了甚至当所有工件具有单位权时,这两个模型都是强NP困难的.但当代理数给定时,这两个问题都可在拟多项式时间解决,并且当工件具有单位权时,可在多项式时间解决.进一步证明当代理数固定时,两个问题都有FPTAS算法.     

Multiple criteria decision making method based on normal interval‐valued intuitionistic fuzzy generalized aggregation operator

On the basis of the normal intuitionistic fuzzy numbers (NIFNs), we proposed the normal interval‐valued intuitionistic fuzzy numbers (NIVIFNs) in which the values of the membership and nonmembership were extended to interval numbers. First, the definition, the properties, the score function and accuracy function of the NIVIFNs are briefly introduced, and the operational laws are defined. Second, some aggregation operators based on the NIVIFNs are proposed, such as normal interval‐valued intuitionistic fuzzy weighted arithmetic averaging operator, normal interval‐valued intuitionistic fuzzy ordered weighted arithmetic averaging operator, normal interval‐valued intuitionistic fuzzy hybrid weighted arithmetic averaging operator, normal interval‐valued intuitionistic fuzzy weighted geometric averaging operator, normal interval‐valued intuitionistic fuzzy ordered weighted geometric averaging operator, normal interval‐valued intuitionistic fuzzy hybrid weighted geometric averaging operator, and normal interval‐valued intuitionistic fuzzy generalized weighted averaging operator, normal interval‐valued intuitionistic fuzzy generalized ordered weighted averaging operator, normal interval‐valued intuitionistic fuzzy generalized hybrid weighted averaging operator, and some properties of these operators, such as idempotency, monotonicity, boundedness, commutativity, are studied. Further, an approach to the decision making problems with the NIVIFNs is established. Finally, an illustrative example is given to verify the developed approach and to demonstrate its practicality and effectiveness. © 2015 Wiley Periodicals, Inc. Complexity 21: 277–290, 2016     

An Integrated Fuzzy Analytic Hierarchy Process (AHP) Model for Studying Significant Factors Associated with Frequent Lane Changing

Frequent lane changes cause serious traffic safety concerns, which involve fatalities and serious injuries. This phenomenon is affected by several significant factors related to road safety. The detection and classification of significant factors affecting lane changing could help reduce frequent lane changing risk. The principal objective of this research is to estimate and prioritize the nominated crucial criteria and sub-criteria based on participants’ answers on a designated questionnaire survey. In doing so, this paper constructs a hierarchical lane-change model based on the concept of the analytic hierarchy process (AHP) with two levels of the most concerning attributes. Accordingly, the fuzzy analytic hierarchy process (FAHP) procedure was applied utilizing fuzzy scale to evaluate precisely the most influential factors affecting lane changing, which will decrease uncertainty in the evaluation process. Based on the final measured weights for level 1, FAHP model estimation results revealed that the most influential variable affecting lane-changing is ‘traffic characteristics’. In contrast, compared to other specified factors, ‘light conditions’ was found to be the least critical factor related to driver lane-change maneuvers. For level 2, the FAHP model results showed ‘traffic volume’ as the most critical factor influencing the lane changes operations, followed by ‘speed’. The objectivity of the model was supported by sensitivity analyses that examined a range for weights’ values and those corresponding to alternative values. Based on the evaluated results, stakeholders can determine strategic policy by considering and placing more emphasis on the highlighted risk factors associated with lane changing to improve road safety. In conclusion, the finding provides the usefulness of the fuzzy analytic hierarchy process to review lane-changing risks for road safety.     

Multi-Decision-Makers Equalizer: A Multiobjective Decision Support System for Multiple Decision-Makers

In this paper we present a decision support system that helps to solve multiobjective decision problems considering a multi decision-makers framework. By an iterative procedure this system looks for a single solution that satisfies all decision-makers equally. The negotiation process requires that each decision-maker trade certain benefits in some of the objectives being analyzed for benefits in others. Finally a compromise solution should be obtained.