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Journal ArticleDOI

Optimizing the capital rationing decision with uncertain returns

31 Mar 2016-The Engineering Economist (Taylor & Francis)-Vol. 61, Iss: 2, pp 128-143
TL;DR: In this paper, a new optimization model for capital rationing with uncertain project returns is developed to maximize the probability of meeting a predefined target return by selecting a feasible set of projects subject to budget constraints in multiple time periods.
Abstract: In this article, we develop a new optimization model for capital rationing with uncertain project returns. Our model maximizes the probability of meeting a predefined target return by selecting a feasible set of projects subject to budget constraints in multiple time periods. We employ a mixed-integer nonlinear algorithm recently developed in the optimization field to solve the resulting nonconvex optimization problem to optimality. Our model and solution methods are tested and validated through a comprehensive computational experiment. Several managerial insights are obtained about the impact of available budget and target return on the optimal solutions. Notably, we have found that increasing target return may not necessarily result in an increase in optimal total expected return of the selected projects. Our model and solution method offer a unified and computationally tractable approach to precisely quantify the tradeoff between project returned and risk.

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Citations
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Journal ArticleDOI
TL;DR: The aim of this research is to provide a solution for incorporating industry-based selected soft data in the project ranking process and took the structured system of criteria identified from the petroleum industry.
Abstract: Project ranking based on project value is an essential management task for organizations that face resource bottlenecks. Project value focuses on the hard elements of projects that can be expressed...

12 citations

Dissertation
01 Jan 2018

8 citations


Cites background from "Optimizing the capital rationing de..."

  • ...Second, SACCOs in Kenya operate in a capital rationing environment (Wambua, 2017), which is defined as the placing of financial restrictions on the amount of money that can be invested in projects with positive net present value (Mai & Li, 2016; Osmundsen, Løvås, & Emhjellen, 2017)....

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01 Jan 2015
TL;DR: In this paper, a semi-structured questionnaire survey was conducted to gather empirical findings with the selected sample and it was revealed there is a high tendency towards adopting CBTs to evaluate the projects in Sri Lanka commercial sector.
Abstract: Capital Budgeting (CB) is one of the most important areas of firms’ decision making process that contributes to long term growth of the firm. Various Capital Budgeting Techniques (CBTs) are being widely used among financial expertise. Several techniques are commonly used to evaluate capital budgeting projects such as Discounted Cash Flow techniques such as Net Present Value (NPV), Internal Rate of Return (IRR) and Profitability Index (PI)) and Non-Discounted Cash Flow techniques such as Payback Period (PP) and Accounting Rate of Return (ARR)). Recent studies highlighted that financial managers favor methods such as the NPV, IRR or PP techniques (Lawrence, et al., 1997). The use of techniques is varying with different factors including organizations, managers, and size of the project. This study particularly finds the Capital Budgeting Techniques (CBT) practiced in Sri Lankan commercial sector organizations. A semi-structured questionnaire survey was conducted to gather empirical findings with the selected sample. It was found that majority of the firms are using NPV as a primary CBT while the second is given to PP and IRR respectively. Some firms adopt more than one technique to be a primary tool and it was highlighted that NPV and IRR as the most commonly used combination in project evolutions. The study found that majority of the firms adopts Weighted Average Cost of Capital (WACC) as an independent measure of cost of capital. It was revealed there is a high tendency towards adopting CBTs to evaluate the projects in Sri Lankan commercial sector.

1 citations

References
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BookDOI
27 Jun 2011
TL;DR: This textbook provides a first course in stochastic programming suitable for students with a basic knowledge of linear programming, elementary analysis, and probability to help students develop an intuition on how to model uncertainty into mathematical problems.
Abstract: The aim of stochastic programming is to find optimal decisions in problems which involve uncertain data. This field is currently developing rapidly with contributions from many disciplines including operations research, mathematics, and probability. At the same time, it is now being applied in a wide variety of subjects ranging from agriculture to financial planning and from industrial engineering to computer networks. This textbook provides a first course in stochastic programming suitable for students with a basic knowledge of linear programming, elementary analysis, and probability. The authors aim to present a broad overview of the main themes and methods of the subject. Its prime goal is to help students develop an intuition on how to model uncertainty into mathematical problems, what uncertainty changes bring to the decision process, and what techniques help to manage uncertainty in solving the problems.In this extensively updated new edition there is more material on methods and examples including several new approaches for discrete variables, new results on risk measures in modeling and Monte Carlo sampling methods, a new chapter on relationships to other methods including approximate dynamic programming, robust optimization and online methods.The book is highly illustrated with chapter summaries and many examples and exercises. Students, researchers and practitioners in operations research and the optimization area will find it particularly of interest. Review of First Edition:"The discussion on modeling issues, the large number of examples used to illustrate the material, and the breadth of the coverage make'Introduction to Stochastic Programming' an ideal textbook for the area." (Interfaces, 1998)

5,398 citations

Book
24 Apr 2009

1,364 citations


"Optimizing the capital rationing de..." refers background in this paper

  • ...Another line of research applies the stochastic programming (SP, (Birge and Louveaux 2011)) methodologies to optimize capital rationing decision under uncertainty....

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Journal ArticleDOI
TL;DR: This paper facilitates the reliable use of nonlinear convex relaxations in global optimization via a polyhedral branch-and-cut approach and proves that, if the convexity of a univariate or multivariate function is apparent by decomposing it into convex subexpressions, the relaxation constructor automatically exploits this convexITY in a manner that is much superior to developing polyhedral outer approximators for the original function.
Abstract: A variety of nonlinear, including semidefinite, relaxations have been developed in recent years for nonconvex optimization problems. Their potential can be realized only if they can be solved with sufficient speed and reliability. Unfortunately, state-of-the-art nonlinear programming codes are significantly slower and numerically unstable compared to linear programming software.In this paper, we facilitate the reliable use of nonlinear convex relaxations in global optimization via a polyhedral branch-and-cut approach. Our algorithm exploits convexity, either identified automatically or supplied through a suitable modeling language construct, in order to generate polyhedral cutting planes and relaxations for multivariate nonconvex problems. We prove that, if the convexity of a univariate or multivariate function is apparent by decomposing it into convex subexpressions, our relaxation constructor automatically exploits this convexity in a manner that is much superior to developing polyhedral outer approximators for the original function. The convexity of functional expressions that are composed to form nonconvex expressions is also automatically exploited.Root-node relaxations are computed for 87 problems from globallib and minlplib, and detailed computational results are presented for globally solving 26 of these problems with BARON 7.2, which implements the proposed techniques. The use of cutting planes for these problems reduces root-node relaxation gaps by up to 100% and expedites the solution process, often by several orders of magnitude.

1,205 citations


"Optimizing the capital rationing de..." refers methods in this paper

  • ...We employ a computational algorithm developed in mathematical programming, called the polyhedral branch-and-cut algorithm (Tawarmalani and Sahinidis 2005), to obtain optimal solution for the problem at hand....

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Book
05 Oct 1995
TL;DR: In this article, the authors present the foundations of nonlinear operations, including convex analysis, duality theory, mixed-integer linear optimization, and mixed-Integer nonlinear optimization.
Abstract: Introduction 1. Convex Analysis 2. Fundamentals of Nonlinear Operations 3. Duality Theory 4. Mixed-Integer Linear Optimization 5. Mixed-Integer Nonlinear Optimization 6. Process Synthesis 7. Heat Exchanger Network Synthesis 8. Distillation-Based Separation Systems Synthesis 9. Synthesis of Reactor Networks and Reactor-Separator-Recycle Systems

1,054 citations


"Optimizing the capital rationing de..." refers background in this paper

  • ...Due to the non-convex form of the objective function (5), it will be difficult for typical branch-and-bound based mixed-integer nonlinear programming (MINLP) methods to work properly and prove optimality (Floudas 1995), because these methods often rely on the convexity assumption of the model....

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Journal ArticleDOI
Kent D. Miller1
TL;DR: In this paper, a framework for categorizing the uncertainties faced by firms operating internationally and outlining both financial and strategic corporate risk management responses is proposed, which is based on the analysis of risk in the international management literature to the exclusion of other interrelated uncertainties.
Abstract: Treatments of risk in the international management literature largely focus on particular uncertainties to the exclusion of other interrelated uncertainties. This paper develops a framework for categorizing the uncertainties faced by firms operating internationally and outlines both financial and strategic corporate risk management responses.

1,017 citations


"Optimizing the capital rationing de..." refers background in this paper

  • ...(Miller 1992) proposed an uncertainty framework with three general types of uncertainty: general uncertainties affecting all companies (e.g., inflation, interest, exchange rate), industry-specific uncertainties impacting some specific industries (e.g., input market, output market, competitive), and…...

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