基于CI-TOPSIS的梯形直觉模糊多准则群决策分类方法

模糊群决策分类方法广泛应用于政治、经济与社会生活各个领域,可有效避免个人知识与经验局限性所导致的决策失误。针对信息不完备的多准则群决策问题,提出基于CI-TOPSIS的梯形直觉模糊多准则群决策分类方法。首先,给出梯形直觉模糊集及广义梯形直觉模糊几何聚类算子,兼顾考虑群决策中相应依赖属性与决策者的决策偏好。其次,给出基于离散Choquet积分的TOPSIS算子（CI-TOPSIS）,以此为基础,进一步给出基于CI-TOPSIS的梯形直觉模糊多准则群决策分类步骤,用于确定具有最大可信度群体一致案例比较信息集,并逐步引导决策者给出部分及全部方案的精确分类,充分考虑模糊决策环境下决策者偏好与案例比较信息的级别关系。最后,通过一个投资决策实例对所提出的多准则分类方法进行验证。实例分析表明：该方法克服了决策过程中信息的遗漏,充分保留了决策过程中信息的完备性,更适用于直觉模糊群决策环境下的决策实践,是一种非常有效和科学的方法,可应用推广到更多决策领域。本文所得结论,对于有效解决多人多投资方案的群决策问题,具有一定的借鉴意义。     

外商直接投资区位选择与风险分析

本文提出一种新的基于组合熵权TOPSIS方法的多目标决策模型,综合考虑市场、成本、聚集和制度等相关因素,对山东省17个地区的经济发展水平及其与外商直接投资区位选择关系进行分析。在模型中,我们首先应用熵权法得到各评价准则和因素的相对权重,然后应用TOPSIS方法对山东省17个地区进行排序。本文还结合实例说明如何将所提出的方法应用到外商直接投资在中国的区位选择问题。此外,我们还进行了敏感性分析,以判断各评价准则受权重的影响程度。研究结果和实例分析表明基于组合熵权TOPSIS方法在外商直接投资区位选择分析中是有效和可行的。     

Budgets for integrating decentralized investment and production planning

Planning for an economic enterprise can be dichotomized into short-run production planning and longer-run investment planning. Usually these problems are treated as if they were separate, if not independent. This paper briefly reviews the separate approaches to optimal production decision making and investment planning, ‘fusing’ these models in order to consider the two issues simultaneously. The resulting ‘fused’ model is used to illustrate several difficulties which result from an intuitive synthesis of the independent solutions of the production problem and the investment problem. An integrated model is presented representing a centralized simultaneous solution for decision variables from the two functional fields. The paper compares and contrasts the synthesis of separate functional models to the decomposition of a simultaneous model of those functional areas. A result of this comparison is a theoretical justification for operating budgets and revenue targets as organizational mechanisms for achieving coordinated plans among decentralized planning units. Further, the set of conditions are identified under which the two approaches to simultaneous decision making are equivalent.     

Supplier selection with multiple criteria in volume discount environments

Supplier selection is a multi-criteria decision making problem which includes both qualitative and quantitative factors. In order to select the best suppliers it is necessary to make a trade-off between these tangible and intangible factors some of which may conflict. When business volume discounts exist, this problem becomes more complicated as, in these circumstances, buyer should decide about two problems: which suppliers are the best and how much should be purchased from each selected supplier. In this article an integrated approach of analytical hierarchy process improved by rough sets theory and multi-objective mixed integer programming is proposed to simultaneously determine the number of suppliers to employ and the order quantity allocated to these suppliers in the case of multiple sourcing, multiple products, with multiple criteria and with supplier's capacity constraints. In this context, suppliers offer price discounts on total business volume, not on the quantity or variety of products purchased from them. A solution methodology is presented to solve the multi-objective model, and the model is illustrated using two numerical examples.     

Multiobjective investment planning under uncertainty

In this paper we consider the relevance of various planning methods and decision criteria to multiobjective investment planning under uncertainty. Assuming that a natural reaction to uncertainty is to operate so as to leave open as many good options as possible (as opposed to maximizing subjective expected utility) we argue that the planning process should concentrate on analyzing the effects of the initial decision, and that for this exercise the classical methods of mixed integer programming are inappropriate. We demonstrate how the technique of dynamic programming can be extended to take account of multiple objectives and use dynamic programming as a framework in which we analyze the robustness of an initial decision in the face of various types of uncertainty. In so doing we also analyze the risks involved in both the planning and decision making functions.     

期权动态套期保值双相机决策模型及实证研究

金融市场具有多变性,投资者一般需要根据市场情况动态地改变套期保值策略,使套期保值组合价格波动的风险被对冲掉。因此,有必要建立期权动态套期保值模型,得到动态的最优期权头寸,这意味着投资者需要按照模型所得到的头寸动态调仓才能达到风险最小的目的。然而,买入期权进行套期保值需要支付期权金成本,也就是投资者为了达到风险最小化的目的需要付出成本代价。那么,付出的代价是否“划算”是投资者面临的一个问题。此外,买入欧式看跌期权可以规避现货价格下跌的风险,但欧式期权只有到到期日时才能被执行,而投资者不一定要持有期权直到到期日。于是,投资者在投资期间选择何时退出是期权动态套期保值的另一个问题。 针对传统的期权套期保值策略存在错失退出良机和调仓过于频繁的问题,提出退出和调仓双相机决策准则,进一步优化传统套期保值策略。在满足预算、预期收益、头寸约束条件下,建立基于在险价值的最优期权动态套期保值模型,得到传统动态套期保值策略。在此基础上,基于经济价值视角将风险和成本代价统一化度量,利用期末绩效评价提出退出和调仓双相机决策准则,进一步修正期权套期保值策略。利用上证50ETF及以上证50ETF为标的的期权开展实证研究。 研究结果表明,运用退出相机准则提供了提前退出投资的参考时间点,运用调仓相机准则通过减少不必要的调仓降低调仓成本。通过对比发现传统的期权动态套期保值策略存在缺陷,运用双相机抉择的期权套期保值策略能够获得更有效率的套期保值结果。利用退出相机提供7个参考退出交易日,若在这些交易日选择退出,投资者将获得比较大的利润,利用调仓相机后增加了收益。 考虑双相机决策的期权最优套期保值模型改进了传统模型的单一决策,提出了更有效的风险控制策略,为投资者提供决策参考具有实际意义。     

Decision Making Under Uncertainty—An Example for Seismic Risk Management

Decision-making techniques are used to select the "best" alternatives under multiple and often conflicting criteria. Multicriteria decision making (MCDM) necessitates to incorporate uncertainties in the decision-making process. The major thrust of this article is to extend the framework proposed by Yager^{( 1 )} for multiple decisionmakers and fuzzy utilities (payoffs). In addition, the concept of expert credibility factor is introduced. The proposed approach is demonstrated for an example of seismic risk management using a heuristic hierarchical structure. A step-by-step formulation of the proposed approach is illustrated using a hypothetical example and a three-story reinforced concrete building.     

中国风电固定上网电价政策的实物期权理论与实证分析

本文使用实物期权方法研究中国目前实施的风电固定上网电价政策。首先说明风电项目投资的实物期权原理,并建立风电固定上网电价政策实物期权模型。然后,从理论上证明了风电最优投资电价与上网电价波动率成正比(固定上网电价理论依据,即政府为了最大限度激励投资者,使得上网电价波动率等于0);最优投资电价与上网电价期望增长率成正比(固定上网电价调整理论依据)。最后,选取河北张北油篓沟元山子风电场工程项目进行实证分析,通过上网电价期望增长率调整的数值分析得到中国风电上网电价平均每年降低幅度应该为1%左右。本文为我国可再生能源电价调整提供参考。     

An application of the AHP in vendor selection of a telecommunications system

Vendor selection of a telecommunications system is an important problem to a telecommunications company as the telecommunications system is a long-term investment for the company and the success of telecommunications services is directly affected by the vendor selection decision. Furthermore, the vendor selection of a telecommunications system is a complex multi-person, multi-criteria decision problem. The group decision-making process can be improved by a systematic and logical approach to assess priorities based on the inputs of several people from different functional areas within the company. The analytic hierarchy process (AHP) can be very useful in involving several decision-makers with different conflicting objectives to arrive at a consensus decision. In this paper, an AHP-based model is formulated and applied to a real case study to examine its feasibility in selecting a vendor for a telecommunications system. The use of the proposed model indicates that it can be applied to improve the group decision making in selecting a vendor that satisfies customer specifications. Also, it is found that the decision process is systematic and that using the proposed AHP model can reduce the time taken to select a vendor.     

Data and Model Management in a Generalized MCDM-DSS*

Drawing upon the choice models developed in the multiple criteria decision making (MCDM) area, this paper proposes an architecture for designing an intelligent decision support system (DSS) that is intended to aid in making choices among multiple alternatives along multiple dimensions. It argues that effective support can be provided to the decision maker when the knowledge-based DSS is capable of dynamically selecting choice models appropriate to the domain and context of a particular problem being specified by the decision maker, and of properly applying them to the problem solution. Development of a prototype intended to partially represent application of the architecture is described. The paper concludes with suggestions for research extensions.     

A Study on a Sequential One‐Defender‐N‐Attacker Game

Government usually faces threat from multiple attackers. However, in the literature, researchers often model attackers as one monolithic player who chooses whether to attack, how much investment to spend, and on which target, instead of treating multiple attackers as independent agents. This modeling strategy may potentially cause suboptimal defense investment if the attackers have vastly different interests and preferences and may not be combined as one in theory. In this article, we develop a sequential game with complete information. This model considers one defender explicitly dealing with multiple unmergeable attackers. Thorough numerical experiments are conducted using ratio and exponential contest success functions under different scenarios. The result is also contrasted with the corresponding single attacker model to study the effect of mishandling multiple attackers. The propositions and observations drawn from the numerical experiments provide insights for government decision making with a better understanding of the attackers' behavior.     

基于产品新鲜度要求的保鲜成本投资与数量集配策略联合决策研究

文章以提供生鲜产品运输配送服务的物流企业为研究对象,考虑生鲜产品质量腐蚀特性,应用随机更新理论建立基于下游零售商产品新鲜度水平要求的保鲜投资与物流集配联合决策随机模型。模型分析指出单位时间的运输成本、集配惩罚成本与保鲜投入成本随保鲜投资决策与物流集配决策变化的内在规律。数值分析指出保鲜投资、物流集配及其联合决策的有效性和产品、成本、需求环境等参数与这些环境参数同时变化对保鲜投资决策、集配决策与企业运营成本的影响。     

Economic ordering policy of deteriorated item for vendor and buyer: An integrated approach

This study develops an economic ordering policy of a deteriorating item with a constant production and demand rate. By considering the view of both the vendor and buyer, a mathematical model subject to single-vendor-single-buyer and multiple deliveries per order is developed. It can be shown that the integrated approach results in an impressive cost-reduction compared with an independent decision by the buyer.     

A Framework for the Analysis of Error in Conjunctive,Multi-Criteria,Satisficing Decision Processes*

This paper examines the impact of certain types of error on ad hoc, unstructured decision making that incorporates a satisficing strategy in a multi-criteria context using the conjunctive rule. The impacts of error in evaluation and of error in minimal or satisficing levels are systematically modelled for each of the decision criteria. Error functions, analytical expressions, and procedures are developed to obtain information such as the likelihood of correct decision making in the presence of evaluation and minimal criteria level error. These are applied to a specific research design, which is then analyzed. This highlights certain features of decision making in a satisficing context, such as the importance of keeping the number of decision criteria to a minimum. The results yield various insights, some of which confirm information obtained from previous analyses. A major advantage of the framework presented is that it can provide quantitative measurements which support ideas previously couched in qualitative terms only. Although the framework is applied in the context of decision making that uses the conjunctive rule in the case of multiple criteria, other satisficing strategies can be accommodated as well.     

A framework of decision making for technological change

The first article in this series2 drew a distinction between the costs of line operations- or current outputs—and those costs devoted to investment, or future outputs. As investment encompasses technological change—in practice it is dominated by it—this article examines some of the broader issues underlying decisions to invest and describes in outline a study being made of the economic criteria that are relevant to such decisions. In the longer term the objective is to develop a procedure or framework of criteria to assist the process of decision making; and this would include a frame of reference—a set of statistical time-series and analyses designed for the purpose.     

Earnings per share is a poor indicator of performance

One of the greatest dangers in corporate financial planning is failing to separate investment decision making from financial policy, because poor quality investments can appear to be desirable as a result of the particular financing vehicle employed. Management's focus of attention should not be rates of growth and earnings per share or return on net worth. Rather, the most important measure of corporate performance is the rate of return on total capital employed. The paper identifies the dangers of employing an earnings per share criterion for evaluating corporate performance, and suggests an alternative: focusing on a company's free cash flow, net operating profits after taxes minus the amount of new capital investment required in order to generate future profits. The author presents an analytical framework employing his free cash flow concept which can be applied to pricing and financing acquisitions.     

An analytic hierarchy process based simulation model for entry mode decision regarding foreign direct investment

A methodology is developed for ranking entry mode alternatives encountered by individual firms considering foreign direct investment (FDI). The methodology deals with the risks and uncertainties related to FDI. The analytic hierarchy process (AHP) is used to solve the multiple criteria decision-making problem using input from a firm's management. A simulation approach is incorporated into the AHP to handle the uncertainty considerations encountered in an FDI environment. The uncertainties include: (1) uncertainty regarding the future characteristics of the FDI decision making environment, (2) uncertainty associated with the decision maker's judgment regarding pairwise comparisons necessitated by the AHP.     

FAMCDM: A fusion approach of MCDM methods to rank multiclass classification algorithms

Various methods and algorithms have been developed for multiclass classification problems in recent years. How to select an effective algorithm for a multiclass classification task is an important yet difficult issue. Since the multiclass algorithm selection normally involves more than one criterion, such as accuracy and computation time, the selection process can be modeled as a multiple criteria decision making (MCDM) problem. While the evaluations of algorithms provided by different MCDM methods are in agreement sometimes, there are situations where MCDM methods generate very different results. To resolve this disagreement and help decision makers pick the most suitable classifier(s), this paper proposes a fusion approach to produce a weighted compatible MCDM ranking of multiclass classification algorithms. Several multiclass datasets from different domains are used in the experimental study to test the proposed fusion approach. The results prove that MCDM methods are useful tools for evaluating multiclass classification algorithms and the fusion approach is capable of identifying a compromised solution when different MCDM methods generate conflicting rankings.     

只有输出的广义样本区间DEA模型

在应用多个绩效指标综合评价决策单元有效性时，决策者常常把这些决策单元与另外预先指定的标准（样本单元）进行比较。由于客观事物的复杂性和不确定性导致样本单元和决策单元的指标信息有时必须用区间数的形式给出。针对区间数指标信息的综合评价问题，本文通过分解的方法讨论样本单元和决策单元指标信息为区间数时用广义DEA模型评价决策单元有效性的方法，并相应地构建了只有输出的广义区间DEA模型。同时，对模型的含义、求解以及性质等进行了分析。之后，探讨了该方法在决策单元有效性分类和排序中的应用。最后，通过实例表明该方法的可行性和有效性。