模糊环境下资金预算的期望净现值模型

资金预算问题是指对一项投资机会是否应该付诸实施进行判断.净现值方法(NPV)一直是现代资本预算方法的传统核心内容.将传统的净现值方法扩展到模糊环境下,讨论了当现金流入和现金流出为模糊变量情况下,如何选择最优的项目.建立了模糊环境下的均值NPV模型,并设计了基于模糊模拟的遗传算法,给出了模型问题的一般解决方法.     

The 0–1 knapsack problem with multiple choice constraints

In this paper we consider the 0–1 knapsack problem with multiple choice constraints appended. Such a problem may arise in a capital budgeting context where only one project may be selected from a particular group of projects. Thus the problem is to choose one project from each group such that the budgetary constraint is satisfied and the maximum return is realized. We formulate two branch and bound algorithms which use two different relaxations as the primary bounding relaxations. In addition, theoretical results are given for a simple reduction in the number of variables in the problem.     

存在借贷资金的随机资金预算问题研究

讨论了企业运用自有资金及银行贷款进行投资时的资金预算问题,与以往的研究不同,本文假设投资支出、年投资收益以及银行贷款都为随机变量,而且,文章的研究并不要求待选的投资项目具有相同的投资期或具有相同的寿命周期.给出了随机环境下净现值收益的期望值模型及期望值目标规划模型,并设计了基于随机模拟的遗传算法,给出了模型的一般解决方法,此外,还提供了两个数值例子,用以说明建模思想,并例证算法的有效性.     

A Portfolio Approach to Capital Budgeting: An Application to the Expansion to Additional Product Lines

The importance of the covariance of returns between capital assets is one of the basic principles of modern portfolio theory. An investor should seek capital assets which have negative covariance of returns, or if such capital assets are not available, capital assets with low covariance should be sought for a portfolio. From the variance-covariance structure of returns of the capital assets and the expected returns for each capital asset, a risk-reward trade-off or efficient frontier can be generated. The trade-off represents the minimum risk, as measured by portfolio variance, that could be incurred to realize a desired rate of return for the portfolio. This concept applies to a portfolio of capital budgeting projects as well as to a portfolio of securities. This paper demonstrates how this concept of portfolio diversification can be applied to a capital budgeting problem. The problem involves an actual problem faced by a U.S. distributor who must decide whether to expand sales into one of two industries. Quadratic programming is used to generate the risk-reward relationships and it is shown that the entry into one industry clearly provides a superior risk-reward relationship than entry into the other industry and compared to the company's present sales policy.     

Logrolling and budget allocation games

In this paper we approach the concept of logrolling by examining a voting system where choices are made among sets of competing projects as a game in characteristic function form. We translate the question: “Will there be prices for votes on different projects which clear the market?” into a different, but equivalent question: “Is the formal game we have described amarket game?” We show that in general the answer is no, unless all voters have virtually the same preferences.     

Chance-constrained programming models for capital budgeting with NPV as fuzzy parameters

In an uncertain economic environment, experts’ knowledge about outlays and cash inflows of available projects consists of much vagueness instead of randomness. Investment outlays and annual net cash flows of a project are usually predicted by using experts’ knowledge. Fuzzy variables can overcome the difficulties in predicting these parameters. In this paper, capital budgeting problem with fuzzy investment outlays and fuzzy annual net cash flows is studied based on credibility measure. Net present value (NPV) method is employed, and two fuzzy chance-constrained programming models for capital budgeting problem are provided. A fuzzy simulation-based genetic algorithm is provided for solving the proposed model problems. Two numerical examples are also presented to illustrate the modelling idea and the effectiveness of the proposed algorithm.     

A mixed-integer goal programming model for nursing service budgeting

This paper presents a mixed-integer goal programming model for expense budgeting in a hospital nursing department. The model incorporates several different objectives based upon such considerations as cost containment and providing appropriate nursing hours for delivering quality nursing care. Also considered are possible trade-offs among full-time, part-time and overtime nurses on weekdays as well as weekends. The budget includes vacation, sick leave, holiday, and seniority policies of a hospital and various constraints on a hospital nursing service imposed by nursing unions. The results are based upon data from a study hospital and indicate that the model is practical for budgeting in a hospital nursing department.     

Financial risk of project's cost

In this paper we will examine the effects of uncertainty of investment costs on the expected gain and budget allocation of a decision-maker. These effects are studied using the relationship between riskiness and stochastic dominance. Results and examples are provided for the case of budgeting one project. Furthermore, the problem of centralized vs. non-centralized budget allocation forn identically independent distributed projects is discussed.     

The Future of Logic: Foundation-Independence

Throughout the twentieth century, the automation of formal logics in computers has created unprecedented potential for practical applications of logic—most prominently the mechanical verification of mathematics and software. But the high cost of these applications makes them infeasible but for a few flagship projects, and even those are negligible compared to the ever-rising needs for verification. One of the biggest challenges in the future of logic will be to enable applications at much larger scales and simultaneously at much lower costs. This will require a far more efficient allocation of resources. Wherever possible, theoretical and practical results must be formulated generically so that they can be instantiated to arbitrary logics; this will allow reusing results in the face of today’s multitude of application-oriented and therefore diverging logical systems. Moreover, the software engineering problems concerning automation support must be decoupled from the theoretical problems of designing logics and calculi; this will allow researchers outside or at the fringe of logic to contribute scalable logic-independent tools. Anticipating these needs, the author has developed the Mmt framework. It offers a modern approach towards defining, analyzing, implementing, and applying logics that focuses on modular design and logic-independent results. This paper summarizes the ideas behind and the results about Mmt. It focuses on showing how Mmt. provides a theoretical and practical framework for the future of logic.     

工期索赔中的难题

针对重大工程计划中工期索赔的责任划分难题,本文根据公路建设中的实际案例,发现了“工期索赔分摊”中的奇怪现象。首先,揭示了“提前完成任务”不但可能得不到“奖励”,反而可能要被“罚款”;其次,揭示了关键工序的工期提前完成较少时,会得到“奖励”,但提前得太多,则反而会被“罚款”。然后,给出了解决这些奇怪现象的解释和方法。这些现象说明了在处理重大工程计划的“索赔款分摊”时,不能只按传统的原则来处理,必须根据实际情况按新的规则来处理。研究结论对于促进工期索赔的合理分摊有一定的理论意义和现实意义。     

A scoring model for flexible manufacturing systems project selection

This paper presents a method for identifying, evaluating, and prioritizing manufacturing modernization projects. The paper distinguishes between modernization, which contains significant uncertainty, and capital replacement which contains minimal risk. Extending classical capital budgeting analysis, which prioritizes capital replacement projects by the criterion of utility maximization, the model described herein addresses the complexities of non-economic criteria, project interdependence, and uncertainty. Exploiting results from risk-oriented R & D project selection literature, the model incorporates the scores of five additive terms: technology assessment, equipment evaluation, capacity elasticity, cost-budget analysis, and adjusted net present value. The technology and equipment scores are based on evaluative scales. The paper introduces the workload elasticity of capacity statistic for the analysis of forecasted workload and plant capacity. The model analyses expected costs and budget levels in the cost-budge ratio submodel. Finally, the model explicitly incorporates conditional probabilities into the adjustment of NPV, to address interdependency and uncertainty.     

Reliability analysis and optimization of weighted voting systems with continuous states input

Weighted voting systems are widely used in many practical fields such as target detection, human organization, pattern recognition, etc. In this paper, a new model for weighted voting systems with continuous state inputs is formulated. We derive the analytical expression for the reliability of the entire system under certain distribution assumptions. A more general Monte Carlo algorithm is also given to numerically analyze the model and evaluate the reliability. This paper further proposes a reliability optimization problem of weighted voting systems under cost constraints. A genetic algorithm is introduced and applied as the optimization technique for the model formulated. A numerical example is then presented to illustrate the ideas.     

Modelling energy consumption in manufacturing industry

The major effort in energy modelling has been directed to national and global consumption.This paper describes how the techniques of multivariate statistical analysis can be used to model energy consumption in a production environment with varying levels of production activity and weather conditions.The author discusses how the methods were applied by the Operational Research Department at Lancaster University to a manufacturing group of six companies involved in making various products for the engineering and construction industry. The paper identifies the practical issues that arose through the project and describes how the energy models are used for budgeting monthly fuel consumption and for evaluating new energt policies.     

A mean-risk index model for uncertain capital budgeting

This paper discusses the capital budgeting problem of projects using annual cash inflows, cash outflows and initial investment outlays given by experts’ evaluations when no historical data are available. Uncertain variables are used to describe the projects’ parameters. A profit risk index and a capital risk index are proposed, and a mean-risk index model is developed for optimal project selection. In addition, the deterministic forms of the model are given and a solution algorithm is provided. For the sake of illustration, a numerical example is also presented. The results of the example show that both profit risk index and capital risk index are important in investment risk control. However, when the profit risk control requirement is strong, the selected project portfolio may be insensitive to the capital risk constraint; when the profit risk control requirement is moderate, the capital risk constraint plays an important role. The results also show the tendency that when either the tolerable profit risk level or the tolerable capital risk level becomes higher, the obtained expected net present value of the project portfolio becomes larger, which is in agreement with the investment rule that the higher the risk, the higher the return.     

Random utility models with all choice probabilities expressible as ‘functions’ of the binary choice probabilities

Given the absence of non-trivial decision rules which are strategy-proof in the Gibbard-Satterthwaite sense, Peleg and Sen have suggested that one might search for decision rules under which there will be always some Nash equilibrium yielding the same outcome as would be yielded by honest voting. This paper shows that most decision rules based on pairwise comparison will fail to satisfy the requirement of Peleg and Sen if one imposes the additional condition that the relevant Nash equilibrium should consist of undominated voting strategies only (a most reasonable condition in the absence of cooperation). It is also shown that under most decision rules based on pairwise comparisons, it will not be possible either to ensure that the outcome of honest voting will be always an outcome of sophisticated voting (in Farquharson's sense) or to ensure that the outcome of honest voting will be always a core outcome.     

Changing behaviours in defence acquisition: a game theory approach

Why do so many major defence contracts fail to deliver to the contractually agreed performance, time and cost requirements? This paper identifies the conspiracy of optimism as an important factor in the initiation of many projects. Using a combination of Game Theory and participatory workshops, we formulate a theory on the conspiracy of optimism and test it experimentally. This work forms part of a culture and behaviour change initiative within Defence Acquisition involving the Ministry of Defence and many defence contractors.     

Budgeting with bounded multiple-choice constraints

We consider a budgeting problem where a specified number of projects from some disjoint classes has to be selected such that the overall gain is largest possible, and such that the costs of the chosen projects do not exceed a fixed upper limit. The problem has several application in government budgeting, planning, and as relaxation from other combinatorial problems. It is demonstrated that the problem can be transformed to an equivalent multiple-choice knapsack problem through dynamic programming. A naive transformation however leads to a drastic increase in the number of variables, thus we propose an algorithm for the continuous problem based on Dantzig–Wolfe decomposition. A master problem solves a continuous multiple-choice knapsack problem knowing only some extreme points in each of the transformed classes. The individual subproblems find extreme points for each given direction, using a median search algorithm. An integer optimal solution is then derived by using the dynamic programming transformation to a multiple-choice knapsack problem for an expanding core. The individual classes are considered in an order given by their gradients, and the transformation to a multiple-choice knapsack problem is performed when needed. In this way, only a dozen of classes need to be transformed for standard instances from the literature. Computational experiments are presented, showing that the developed algorithm is orders of magnitude faster than a general LP/MIP algorithm.     

Sustainable energy futures: Methodological challenges in combining scenarios and participatory multi-criteria analysis

This paper analyses the combined use of scenario building and participatory multi-criteria analysis (PMCA) in the context of renewable energy from a methodological point of view. Scenarios have been applied increasingly in decision-making about long-term consequences by projecting different possible pathways into the future. Scenario analysis accounts for a higher degree of complexity inherent in systems than the study of individual projects or technologies. MCA is a widely used appraisal method, which assesses options on the basis of a multi-dimensional criteria framework and calculates rankings of options. In our study, five renewable energy scenarios for Austria for 2020 were appraised against 17 sustainability criteria. A similar process was undertaken on the local level, where four renewable energy scenarios were developed and evaluated against 15 criteria. On both levels, the scenario development consisted of two stages: first an exploratory stage with stakeholder engagement and second a modelling stage with forecasting-type scenarios. Thus, the scenarios consist of a narrative part (storyline) and a modeled quantitative part. The preferences of national and local energy stakeholders were included in the form of criteria weights derived from interviews and participatory group processes, respectively. Especially in the case of renewable energy promotion in Austria, the paper systematically analyses the potentials and limitations of the methodology (1) for capturing the complexity of decision-making about the long-term consequences of changes in socio-economic and biophysical systems and (2) for appraising energy futures. The paper concludes that assessing scenarios with PMCA is resource intense, but this methodology captures successfully the context of technology deployment and allows decision-making based on a robust and democratic process, which addresses uncertainties, acknowledges multiple legitimate perspectives and encourages social learning.     

A decision model for interdependent information system project selection

Existing methods for information system (IS) project selection neglect an important aspect of information technology, namely the interdependencies that exist among various IS applications (projects). Recognizing and modeling these project interdependencies provides valuable cost savings and greater benefits to organizations. In this paper, an IS project selection model is developed that identifies and models benefit, resource and technical interdependencies among candidate projects. The proposed model is formulated as a nonlinear 0–1 programming problem and represents a significant addition to existing IS, capital budgeting and R&D project selection models. The model is converted, using linearization techniques, and tested (validated) by applying it to real-world IS project selection data. By comparing the performance of this model with existing project selection models, the contribution of this model is highlighted.     

A Bayesian approach to a sequential three‐decision problem: Voting and the uses of information in electoral choice*

This paper investigates a situation of decision‐making under risk in which an individual must select one of three actions. Substantively, an electoral example in which a citizen must decide how and whether to vote in a two‐candidate election is used to illustrate the argument. Only the value of the consequences of one action, which is to abstain from voting, is known. The expected values of voting for either candidate must be estimated based upon a sample of information. Specifically, we are interested in how one may decide when to stop gathering information and the behavioral consequences of that choice for the voting decision. The dependence of the voting decision on the original ambiguity and magnitude of the expected utilities and on the costs of information is also explored.