Search

This paper introduces a graphical method for valuing options on real asset investments that allow the investor to switch between different operating modes at a single point-in-time. The technique uses mixtures of truncated exponential functions to approximate both the probability density function for project value and the expressions for option value of each alternative. The distribution for project value is transformed into an expected cash flow function for the option under each mode of operation. After determining an optimal exercise strategy, these functions are used to determine the option value. The graphical method allows the option exercise strategy to be communicated effectively through a graphical representation of the expected cash flow functions. A comparison of this approach to the existing binomial lattice method is presented. The efficiency of the graphical method is comparable to the binomial lattice and in some cases accurate solutions can be obtained with less CPU time.

Real Options Analysis (ROA) provides a framework for valuing reactive and proactive managerial flexibility in investment decisions. Estimating the volatility parameter for a real options model is challenging because there are typically no historical returns for the underlying asset and no current market prices. A previously developed method of using simulation to estimate the volatility parameter for a real investment is demonstrated. The effects of serial price correlation and price-demand cross-correlation on volatility parameters developed with this method are explained. Finally, managerial implications of these findings are discussed.

The Colorado legislature recently funded a grant proposal to create “Prospector,” a regional library network. The network, now operational, was a joint project of the University of Northern Colorado and the Colorado Alliance of Research Libraries. The major goals of the project were (1) to create a single digital catalog of the library holdings of the major academic and public library collections in Colorado and make it accessible by anyone from anywhere in the state; and (2) to create an automated borrowing system to facilitate the ability of library patrons to order library materials from home, school, office, or at a local library and arrange for expedited delivery to various locations. This article describes the issues faced and the experiences involved in bringing these goals to fruition.

Many companies in the biotechnology industry have significant valuations despite having no product revenue because their products are in early stages of development. In the past 10–15 years, investors have bid up the stock prices of companies showing promise of developing a blockbuster drug. We explain the decision-tree method and binomial-lattice method (which adds a growth option) and use them to value a biotechnology company, Agouron Pharmaceuticals, as the sum of the values of its drug-development projects. The growth option was added because the development of an initial new molecular entity (NME) is similar to purchasing a call option on the value of a subsequent NME. We compare our computed values of Agouron with actual market values at selected points in time during the development of Agouron's Viracept, a drug used to treat HIV-positive patients.

We use queueing network models to show that with other factors held constant, the transformation of a functional into a cellular layout causes average work-inprocess levels to increase because of a loss in routeing flexibility resulting from the dedication of machines to part families. However, in practice cellular layouts provide important benefits to counteract this loss in routeing flexibility. We use deterministic models to investigate the potential benefits of four characteristics of cellular layouts: (1) operations overlapping, (2) setup time reduction, (3) reductions in move times, and (4) the simultaneous setup of all equipment in a cell. Stochastic operating environments are investigated with simulation models, which provide evidence that these four characteristics will o ffset the reduced routeing flexibility in practice. In addition, the models show that as the congestion level increases, the need also increases to o ffset this loss in routeing flexibility.

This study compares alternative shop loading procedures for cellular and functional layouts in a variety of operating environments. Factors investigated here include: (1) the extent to which the parts in a family follow a unidirectional flow; (2) shop congestion level; (3) the magnitude of delays in moving batches between departments; and (4) whether the shop was labour constrained. Computer simulation was used to compare the combinations of shop layout and loading procedure on the basis of time in system. Important managerial implications are presented for selecting a layout and loading procedure given the operating environment.

Book review of: 'New vocabularies in film semiotics: structuralism, post-structuralism and beyond' by Robert Stam, Robert Burgoyne and Sandy Flitterman‐Lewis (London and New York: Routledge, 1992), 239 pp.

Two problems in linear programming associated with data envelopment analysis (DEA) namely, employing non-archimedean infinitesimals, transcendemals (‘big Ms’) and categorical variables (in a new non-archimedean formulation) are addressed. A new more sophisticated pricing procedure as part of an adjacent extreme point algorithm solves these efficiently in the base field. Employing this in Charnes's non-archimedean simplex algorithm led to a ninefold increase in computational speed on large DEA problems with about 1000 decision-making units. Additionally, computational failures due to cycling and/or conditioning instabilities were eliminated.

A new class of semi-infinite deterministic (‘determinizations’) dominants and relaxations of joint chance-constraints in chance-constrained programming is developed and specialized to zero-order stochastic decision rule situations. Tight constraint relaxations are obtained where only the partial information of means and variances is known. The tight non-linear semi-infinite relaxations are related to an accessible finite subsystem. When the chance constraints involve linear inequalities, for a large class, the non-linear tight system is proved equivalent to a linear program. Its solutions for the Prekopa-Szantai reservoir construction examples agree well with theirs

In contrast to existing sufficient conditions for preservation of efficiency under special perturbations and matrix structural assumptions, sensitivity of the additive model's classifications in data envelopment analysis (DEA) is investigated by means of new DEA formulations focusing on the stability (sensitivity) of an organization's classification (whether efficient or inefficient). The formulations for the additive model are linear programming problems whose solutions yield a particular region of stability, a ‘cell’, in which an organization's classification remains unchanged. The largest such cell can always be easily computed for each organization and additionally theoretically characterized simply as optimal solutions of particular linear programming problems.

Analytic relations between the two representations (half-space and finitely generated) of cones in polyhedral cone-ratio DEA models are derived, which, for useful classes of cases in which they are simple, can make available the advantages of both for analysis and computation. We prove that such transfers between the two may be made through, essentially, the inverse of an associated matrix available in the computation and we provide formulae connecting solutions in the two representations.

A new solution class of T-nondominated efficient outcomes, extending to games with nontopological product strategy sets and multiple payoffs to players, is developed without point-to-set mappings or quasi-variational inequalities. Some essential properties are developed, and two illustrative examples provide comparison to existing notions with respect to Pareto efficiency and generalized Nash equilibria.

The Council on Interracial Books for Children is concerned with bias in children's literature. This article discusses the origins and developments of the organization, the Bulletin it publishes and its controversial role in the world of children's materials.

We discuss a new algorithm for the separable convex programming with linear constraints. This is based on the approximation of the objective function by at most two linear pieces in the neighborhood of the current feasible solution. The two segments will be adaptively defined rather than predecided fixed grids. If3 furthermore, the objective function is differentiable, and one introduces a non-Archimedean infinitesimal, the algorithm generates a sequence of feasible solutions every cluster point of which is an optimal solution. Computational tests on the problem with up to 196 non-linear variables are presented

Defect in the core as a solution to n-person superadditive characteristic function games are examined and the process of achieving a ‘ reasonable- ’ core by changing the value of tho grand coalition is studied. A new unique solution concept, the ‘ homoeore ’, is proposed based on the ‘ homomollifier ’ notion interpreted as the result of implicit bargaining and weighted averages of coalitional worth. Thereby unreasonable cores are excluded but a core-like dominance property on the average is maintained. It also yields a measure of ‘ operational efficiency ’ where the game may be interpreted as an economic situation of decreasing marginal productivity

A method is presented for obtaining minimum discrimination information (M.D.I.) estimates of probability distributions. This involves using an extremal principle of Charnes and Cooper (1974) and, viewing M.D.I, estimation in a dual convex programming framework. The resulting dual convex program is unconstrained and involves only exponential and linear terms, and hence is easily

In place of classical utility conceptions, policy discussions for intergenerational transfers of income involve the balancing of several desirable social goals: maintaining or improving the standard of living of (i) the working popuuion, (ii) the retired population, and (iii) maintaining a stable intergenerational transfer system. The new method of goal focusing achieves both the trade-off analyses of utility function methods at Pareto-efficient points and due accounting for the effects of multiple objectives. A goal-focusing approach is herein developed for the detailed quantitative analysis of intergenerational income transfers of a national social security system.

A special class of the Charnes-Kortanek “convex nucleus” solutions Is studied in which the minimized functional is separable (monotropic). This class includes Euclidean distance, Hellinger measure, Bose-Einstein entropic measure and the Charnes-Cooper relative entropic solutions. It is shown that the dual convex programs are “essentially” unconstrained and that a simple explicit inversion formula connects optimal primal and dual solutions.

A new class of constrained stochastic network models is formulated in a manner that can be used to support a variety of analyses of optimal design modifications for special weapons systems under budgetary and other constraints. Alternative expressions in terms of geometric programming are also explored. These, however, are far more inconvenient to compute or manipulate especially as the model size increases. Component modifications to the B52G system are considered in a prototype example.

A new ‘cone ratio’ data envelopment analysis (DEA) model that substantially generalizes the Charnes-Cooper-Rhodes (CCR) model and the Charnes-Cooper-Thrall approach characterizing its efficiency classes is developed and studied. It allows for infinitely many decision-making units (DM Us) and arbitrary closed convex cones for the virtual multipliers as well as the cone of positivily of the vectors involved. Generalizations of linear programming and polar cone equalizations arc the analytical vehicles employed.

Pincus’ 1968 formula for the (unique) global minimum of a continuous function on a compact set in E n is extended to finite multiple optima and to discrete and special variants. The impact of these on associated ergodic irreducible aperiodic Markov chain computation (Pincus 1970)—currently called ‘simulated annealing’—is exemplified and assessed leading to grave concern about what current simulated annealing processes may converge to, instead of optima.

The problem of deriving lower and upper bounds for integer variables in integer programming problems by means of surrogate constraints is studied. The method of Hammer, Padberg, and Peled is generalized to the use of the whole system of original constraints with strictly sharper results. An equivalent formulation as a zero-sum two person constrained game is also derived, and further conclusions about the sharpness of bounds derived from surrogate constraints are made. (Author)

Extensions of a 'multi-modal' goal-arc EEO model are discussed in the context of prototype studies to check-out the model structure and computational efficiencies using PNET and other computer codes. The model presented provides for the information assistance needed after one has EEO goals to develop the strategies involving trade-offs between internal vs. external recruitment. (Author)

This paper presents a new extremal approach to deriving dual optimization problems with proper duality inequality which simplifies, and generalizes the Fenchel-Rockafellar scheme. Our derivation proceeds in two stages, (i) inequality attainment,(ii) decoupling primal and dual variables, The power and convenience of this approach are exhibited through a new, much simpler derivation of the Charnes-Cooper results for Khinchin-Kullback-Leibler statistical estimation [1], the immediate establishment of the C2 duality for general distributions and its extensions to general linear inequality constraints, plus the development of a new two-person zero-sum game connection.

In this paper we extend our grasp of statistical theory, duality theory, and computational convenience to the general linear inequality situation in K2L (or minimum discrimination information) estimation by exhibiting it as the limit of a simple one parameter sequence of equality problems. Only the finite discrete distribution case is treated here.

Linear programming as a problem in optimizing a linear functional subject to linear inequality constraints is first discussed along with possible uses of the resulting duality relations. Various approaches to dealing with such problems when parts of the data are subject to error are briefly reviewed. Chance constrained programming refers to the class of such cases in which contraint violations are admissible up to pre- assigned probability levels. This topic is elaborated in the context of a ship-chartering problem in which independent normally distributed deviates from the (known) average demands may occur in any of the periods to be considered. Certain additional assumptions (including the use of a specified class of linear decision rules) make it possible to effect reductions first to a nonlinear (mathematical) programming and then to a linear programming problem. The use of the resulting duality relations for evaluating risk and quality levels of planned performance are then briefly examined.

(1955). Generalizations of the Warehousing Model. Journal of the Operational Research Society: Vol. 6, No. 4, pp. 131-172.

The method of iterative weighted least squares can be used to estimate the parameters in a nonlinear regression model. If the dependent variables are observations from a member of the regular exponential family, then under mild conditions it is shown that the IWLS estimates are identical to those obtained using the maximum likelihood principle. An application is provided to illustrate the results.