基于战略导向的项目组合选择优化研究

本文研究了以项目组合的选择实现组织战略目标最大化的问题,将战略目标分解为收益、成本和风险目标,运用模糊集截集原理和目标标准法则把战略目标整合为单个的权衡目标。用梯形模糊数表示项目的不确定参数,并考虑项目间的相互影响关系,建立了基于战略目标的项目组合选择模型,来实现项目组合选择与战略目标的一致。并针对模型提出了遗传算法进行求解,用示例验证了方法的有效性。     

Solving project scheduling problem with the philosophy of fuzzy random programming

Project scheduling problem is to determine the schedule of allocating resources to achieve the trade-off between the project cost and the completion time. In real projects, the trade-off between the project cost and the completion time, and the uncertainty of the environment are both considerable aspects for managers. Due to the complex external environment, this paper considers project scheduling problem with coexisted uncertainty of randomness and fuzziness, in which the philosophy of fuzzy random programming is introduced. Based on different ranking criteria of fuzzy random variables, three types of fuzzy random models are built. Besides, a searching approach by integrating fuzzy random simulations and genetic algorithm is designed for searching the optimal schedules. The goal of the paper is to provide a new method for solving project scheduling problem in hybrid uncertain environments.     

Fuzzy qualitative trigonometry

This paper presents a fuzzy qualitative representation of conventional trigonometry with the goal of bridging the gap between symbolic cognitive functions and numerical sensing & control tasks in the domain of physical systems, especially in intelligent robotics. Fuzzy qualitative coordinates are defined by replacing a unit circle with a fuzzy qualitative circle; a Cartesian translation and orientation are defined by their normalized fuzzy partitions. Conventional trigonometric functions, rules and the extensions to triangles in Euclidean space are converted into their counterparts in fuzzy qualitative coordinates using fuzzy logic and qualitative reasoning techniques. This approach provides a promising representation transformation interface to analyze general trigonometry-related physical systems from an artificial intelligence perspective.Fuzzy qualitative trigonometry has been implemented as a MATLAB toolbox named XTRIG in terms of 4-tuple fuzzy numbers. Examples are given throughout the paper to demonstrate the characteristics of fuzzy qualitative trigonometry. One of the examples focuses on robot kinematics and also explains how contributions could be made by fuzzy qualitative trigonometry to the intelligent connection of low-level sensing & control tasks to high-level cognitive tasks.     

Fuzzy qualitative trigonometry

This paper presents a fuzzy qualitative representation of conventional trigonometry with the goal of bridging the gap between symbolic cognitive functions and numerical sensing & control tasks in the domain of physical systems, especially in intelligent robotics. Fuzzy qualitative coordinates are defined by replacing a unit circle with a fuzzy qualitative circle; a Cartesian translation and orientation are defined by their normalized fuzzy partitions. Conventional trigonometric functions, rules and the extensions to triangles in Euclidean space are converted into their counterparts in fuzzy qualitative coordinates using fuzzy logic and qualitative reasoning techniques. This approach provides a promising representation transformation interface to analyze general trigonometry-related physical systems from an artificial intelligence perspective.Fuzzy qualitative trigonometry has been implemented as a MATLAB toolbox named XTRIG in terms of 4-tuple fuzzy numbers. Examples are given throughout the paper to demonstrate the characteristics of fuzzy qualitative trigonometry. One of the examples focuses on robot kinematics and also explains how contributions could be made by fuzzy qualitative trigonometry to the intelligent connection of low-level sensing & control tasks to high-level cognitive tasks.     

Time-cost trade-off analysis of project networks in fuzzy environments

This paper proposes a novel approach for time-cost trade-off analysis of a project network in fuzzy environments. Different from the results of previous studies, in this paper the membership function of the fuzzy minimum total crash cost is constructed based on Zadeh’s extension principle and fuzzy solutions are provided. A pair of two-level mathematical programs parameterized by possibility level α is formulated to calculate the lower and upper bounds of the fuzzy minimum total crash cost at α. By enumerating different values of α, the membership function of the fuzzy minimum total crash cost is constructed, and the corresponding optimal activity time for each activity is also obtained at the same time. An example of time-cost trade-off problem with several fuzzy parameters is solved successfully to demonstrate the validity of the proposed approach. Since the minimum total crash cost is expressed by a membership function rather than by a crisp value, the fuzziness of parameters is conserved completely, and more information is provided for time-cost trade-off analysis in project management. The proposed approach also can be applied to time-cost trade-off problems with other characteristics.     

Long-term inventory policy-making through fuzzy decision-making models

The inventory policy, meant as a replenishment rule, has a considerable impact on most firms. The paper considers the determination of optimal inventory policy of firms from a global viewpoint of top management. The inventory is represented as a fuzzy system with the fuzzy inventory level as the output, the fuzzy replenishment as the input and fuzzy demand. The control problem is formulated in terms of decision-making in a fuzzy environment with fuzzy constraints imposed on replenishments, a fuzzy goal for preferable inventory levels to be attained and the fuzzy decision as the intersection of fuzzy constraints and the fuzzy goal at subsequent stages. The planning horizon is infinite. The problem is to find an optimal time-invariant strategy relating the optimal replenishments to the current inventory levels, maximizing the membership function of fuzzy decision. The existence of such a strategy is proved and an algorithm for its determination is given. The optimal time-invariant strategy obtained is represented as a fuzzy conditional statement equated with a fuzzy relation which is the firm's optimal fuzzy replenishment rule.     

部分权重信息下对方案有互补偏好的多属性决策法

研究了只有部分权重信息且对方案的偏好信息以模糊互补判断矩阵形式给出的多属性决策问题.首先,基于模糊互补判断矩阵的主观偏好信息,利用转换函数将客观决策信息一致化,建立一个目标规划模型,通过求解该模型得到属性权重,从而利用加性加权法获得各方案的综合属性值,并以此对方案进行排序或择优.提出了一种基于目标规划的多属性决策方法.该方法具有操作简便和易于上机实现的特点.最后,通过实例说明模型及方法的可行性和有效性.     

Target training with soft computing tools

The personal capabilities and intentions of employees indicate their performance within their organization. It is important for the organization to capture this kind of tacit knowledge since the workforce are the true experts in perceiving the organization's current reality and evaluating which assets require development – including themselves as knowledge assets. The collective inner voice of the workforce helps the organization's management to steer the company and its assets in a sustainable direction.This article presents how the collective inner voice of the workforce can be captured and how it can be used for the benefit of the organization and its employees. The objective is to support individuals’ personal aspirations, as well as to save the money, time and resources that an organization spends on personnel training.The focus of this article is on demonstrating a possible soft-computing method used for competency simulation. The process starts with a linguistic self-evaluation conducted by employees, where individuals’ own perception of current and target competence levels is captured. The self-evaluation is conducted with the help of fuzzy logic. Clusters are formed from the result dataset using an unsupervised neural network clustering method: self-organizing maps. A demonstrator tool is then used to perform a “what-if” type of analysis/simulation on the clusters in the results. With the demonstrator tool, employees can roughly test the impact of alternative training scenarios for themselves. For individuals this may open up new directions for self-development, and for organizations this may allow the efficient use of training resources. We tested the approach with a dataset from a real human resource development project among nuclear power plant operators.The case study reveals the potential of soft-computing based collective competency simulation as one part of personnel development projects in the future. Yet the techniques and the demonstrator tool used in this experiment are far from being products that employees could easily use as part of their training project. Possible benefits of the proposed approach are demonstrated in this article.     

An extension of Sharpe's single-index model: portfolio selection with expert betas

This paper presents an approach to the portfolio selection problem based on Sharpe's single-index model and on Fuzzy Sets Theory. In this sense, expert estimations about future Betas of each financial asset have been included in the portfolio selection model denoted as ‘Expert Betas’ and modelled as trapezoidal fuzzy numbers. Value, ambiguity and fuzziness are three basic concepts involved in the model which provide enough information about fuzzy numbers representing ‘Expert Betas’ and that are simple to handle. In order to select an optimal portfolio, a Goal Programming model has been proposed including imprecise investor's aspirations concerning asset's proportions of both, high-and low-risk assets. Semantics of these goals are based on the fuzzy membership of a goal satisfaction set. To illustrate the proposed model a real portfolio selection problem is presented.     

基于模糊—冲突熵的风险性大群体应急决策方法

针对应急决策信息的模糊性以及大群体偏好的冲突性引起决策风险的问题,提出了一种基于模糊—冲突熵的风险性大群体应急决策方法。首先,依据决策者偏好将大群体进行聚类,得到聚集偏好矩阵;其次,提出一个直觉模糊形式的区间直觉模糊距离以减少偏好信息的丢失,同时定义广义直觉模糊数,将二者与前景理论相结合,通过转换得到聚集的直觉模糊前景决策矩阵;再次,构建以决策风险最小化为目标的大群体模糊—冲突熵应急决策模型,计算准则权重,将大群体的前景决策矩阵和准则权重相结合得到方案的综合前景值,并以此对应急方案排序;最后,通过案例的分析与对比验证了所提方法的合理性与有效性。     

European option pricing model in a stochastic and fuzzy environment

The primary goal of this paper is to price European options in the Merton＇s frame- work with underlying assets following jump-diffusion using fuzzy set theory. Owing to the vague fluctuation of the real financial market, the average jump rate and jump sizes cannot be recorded or collected accurately. So the main idea of this paper is to model the rate as a triangular fuzzy number and jump sizes as fuzzy random variables and use the property of fuzzy set to deduce two different jump-diffusion models underlying principle of rational expectations equilibrium price. Unlike many conventional models, the European option price will now turn into a fuzzy number. One of the major advantages of this model is that it allows investors to choose a reasonable European option price under an acceptable belief degree. The empirical results will serve as useful feedback information for improvements on the proposed model.     

Solving a multi-objective multi-skilled manpower scheduling model by a fuzzy goal programming approach

Manpower scheduling is an intricate problem in production and service environments with the purpose of generating fair schedules that consider employers’ objectives and employees’ preferences as much as possible. However, sometimes, vagueness of information related to employers’ objectives and employees’ preferences leads to the fuzzy nature of the problem. This paper presents a multi-objective manpower scheduling model regarding the lack of clarity on the target values of employers’ objectives and employees’ preferences. Hence, a fuzzy goal programming model is developed for the presented model. Afterwards, two fuzzy solution approaches are used to convert the fuzzy goal programming model to two single-objective models. Finally, the results obtained by both single-objective models are compared with each other to select the solution that has the greatest degree of the satisfaction level of employers’ objectives and employees’ preferences.     

基于Fuzzy-Rough-TOPSIS的工程项目投标风险评价模型研究

在工程项目招投标阶段,项目风险评价是建筑施工企业进行投标决策和作出项目选择的重要依据.基于理想化与主客观相结合的思想,提出了一种确定风险评价指标综合权重的方法;采用梯形模糊数处理模糊性信息,并将其与粗集理论和TOPSIS(a technique for order preference by similarity to ideal solution)方法相融合,建立了工程项目风险评价的Fuzzy-Rough-TOPSIS模型.实例运行表明,模型可操作性强,适用于多个项目的风险分析和比较,并能够在一定程度上克服以往模型存在的主观性强、应用条件限制严格等不足.     

Linear programming with fuzzy parameters: An interactive method resolution

This paper proposes a method for solving linear programming problems where all the coefficients are, in general, fuzzy numbers. We use a fuzzy ranking method to rank the fuzzy objective values and to deal with the inequality relation on constraints. It allows us to work with the concept of feasibility degree. The bigger the feasibility degree is, the worst the objective value will be. We offer the decision-maker (DM) the optimal solution for several different degrees of feasibility. With this information the DM is able to establish a fuzzy goal. We build a fuzzy subset in the decision space whose membership function represents the balance between feasibility degree of constraints and satisfaction degree of the goal. A reasonable solution is the one that has the biggest membership degree to this fuzzy subset. Finally, to illustrate our method, we solve a numerical example.     

A multi-objective joint replenishment inventory model of deteriorated items in a fuzzy environment

In this study, a fuzzy multi-objective joint replenishment inventory model of deteriorating items is developed. The model maximizes the profit and return on inventory investment (ROII) under fuzzy demand and shortage cost constraint. We propose a novel inverse weight fuzzy non-linear programming (IWFNLP) to formulate the fuzzy model. A soft computing, differential evolution (DE) with/without migration operation, is proposed to solve the problem. The performances of the proposed fuzzy method and the conventional fuzzy additive goal programming (FAGP) are compared. We show that the solution derived from the IWFNLP method satisfies the decision maker’s desirable achievement level of the profit objective, ROII objective and shortage cost constraint goal under the desirable possible level of fuzzy demand. It is an effective decision tool since it can really reflect the relative importance of each fuzzy component.     

Fuzzy expectation values in multistage optimization problems

The study demonstrates the use of fuzzy expectation values in problems of multistage optimization under uncertainty. A practicable procedure is presented for the case where the optimization objective can be decomposed into a series of single-stage decision goals. Instead of probability theory, the uncertainty resolution is accomplished by fuzzy expectation values. In essence, then, the risk aversion is emboided in the selection of the fuzzy integration measure. If for example, the primary goal of the optimization is to achieve a strict cost minimum, then in the lack of information, a weaker goal can be introduced that corresponds to balancing the anticipated costs to the risk of exceeding these in reality. In a number of common optimization problems the method proposed facilitates a rapid solution with clear information on the risk involved.     

银行保险中的委托-代理人激励模型

本文运用信息经济学里的委托－代理人理论，研究了银行保险中银行对其代理保险的员工激励问题， 建立了将主观绩效评价和客观绩效评价相结合的激励模型，其中主观绩效评价因涉及多因素多层次的模糊评价因素，采用二级模糊综合评判的方法。并将此模型运用于上海地区的银行保险激励的实际问题。     

模糊判断矩阵一致性逼近及排序方法

根据一致性模糊判断矩阵定义,提出了一种求取一致性判断矩阵及方案排序的新方法,该方法是通过建立一个线性目标规划模型来得到排序向量,并相应地得到逼近于决策偏好的一致性判断矩阵,最后给出了一个算例。