RAND Research Topic: Optimization Modeling2020-07-29T16:12:24ZCopyright (c) 2020, The RAND CorporationRAND Corporationhttps://www.rand.org/topics/optimization-modeling.htmlPortfolio Optimization by Means of Multiple Tandem Certainty-Uncertainty SearchesBrian G. Chowhttps://www.rand.org/pubs/research_reports/RR270.html2013-03-15T07:45:00Z2013-03-15T07:45:00ZThis paper describes a new approach and associated search schemes for optimization under uncertainty. Analysts can apply this method to a problem with a significantly larger number of decision variables, uncertain parameters, and uncertain scenarios.An Optimization Approach to Workforce Planning for the Information Technology FieldJohn A. Ausink; Robert Clemence, Jr.; Robert Howe; Sheila E. Murray; Christopher Horn; John D. Winklerhttps://www.rand.org/pubs/monograph_reports/MR1484.html2002-01-01T12:01:48Z2002-01-01T12:01:48ZA new approach to getting the optimal mix of Army information technology personnelA Global Optimization Method for Nonlinear Bilevel Programming ProblemsMahyar A. Amouzegarhttps://www.rand.org/pubs/external_publications/EP19991215.html1999-01-01T00:00:00Z1999-01-01T00:00:00ZNonlinear two-level programming deals with optimization problems in which the constraint region is implicitly determined by another problem.Solving Optimization Problems Subject to a Budget Constraint with Economies of ScaleRichard Hillestadhttps://www.rand.org/pubs/papers/P5207.html1974-01-01T00:00:00Z1974-01-01T00:00:00ZThis paper describes a finite procedure for locating a global minimum of a problem which is linear in the objective and constraints except for one nonlinear constraint which is of the "reverse convex" variety. Implicit Function Theorems for Optimization Problems and for Systems of InequalitiesJames H. Bigelow; Norman Shapirohttps://www.rand.org/pubs/reports/R1036.html1974-01-01T00:00:00Z1974-01-01T00:00:00ZImplicit function formulas for differentiating the solutions of mathematical programming problems satisfying the conditions of the Kuhn-Tucker theorem are motivated and rigorously demonstrated.The Implications of Manpower Supply and Productivity for the Pay and Composition of the Military Force: An Optimization ModelDavid L. Jaquette; Gary R. Nelsonhttps://www.rand.org/pubs/reports/R1451.html1974-01-01T00:00:00Z1974-01-01T00:00:00ZDevelopment of a mathematical model of military manpower used to describe the dynamic flow of personnel within the military system.An Optimization Algorithm for Cluster Analysis.C. D. Roachhttps://www.rand.org/pubs/papers/P4878.html1972-01-01T00:00:00Z1972-01-01T00:00:00ZGiven a set of [N] points and distances between all points, this paper presents an algorithm for determining an optimal partition of the points into [k] mutually exclusive and exhaustive subsets or clusters according to an objective function defined ...Optimization of Price and Quality in Service Systems.John G. Wirthttps://www.rand.org/pubs/papers/P4590.html1971-01-01T00:00:00Z1971-01-01T00:00:00ZDiscussion of techniques for quantitative determination of the optimal prices and service quality in a wide class of systems. A probabilistic demand model sensitive to both price and quality is derived from the microeconomic concept that a consumer ...Searching for the Multiplier in One Constraint Optimization Problems.Bennett L. Fox; Dale M. Landihttps://www.rand.org/pubs/papers/P4121.html1969-01-01T00:00:00Z1969-01-01T00:00:00ZOne-constraint optimization problems are approached via Lagrange multipliers. Sequential search schemes for generating suitable trial multiplier values are compared, and it is shown that, in general, the minimax sequential search is bisection. For ...Discrete Optimization Via Marginal Analysis.Bennett L. Foxhttps://www.rand.org/pubs/papers/P3288-1.html1966-01-01T00:00:00Z1966-01-01T00:00:00ZDiscrete optimization, subject to one constraint, is attacked by Lagrangian analysis. Incremental allocation schemes are given that generate undominated allocations. In an important special case, the complete family of undominated allocations is ge...Successive approximation by quadratic fitting as applied to optimization problemsS. P. Azenhttps://www.rand.org/pubs/research_memoranda/RM5001.html1966-01-01T00:00:00Z1966-01-01T00:00:00ZAn investigation of a technique of solving optimization problems by expanding the original functional about an approximating function to obtain a quadratic function, which can then be solved exactly using dynamic programming. Applications and numeric...Mathematical optimization techniques;[papers]Richard Ernest Bellmanhttps://www.rand.org/pubs/reports/R396.html1963-01-01T00:00:00Z1963-01-01T00:00:00ZMathematical optimization techniques;[papers]On the Use of the Calculus of Variations in Trajectory Optimization ProblemsD. G. Stecherthttps://www.rand.org/pubs/research_memoranda/RM3793.html1963-01-01T00:00:00Z1963-01-01T00:00:00ZA presentation of the methodology required in the use of the calculus of variations and its application to a number of trajectory problems. Some mathematical aspects of optimization problems in engineering.Robert E. Kalabahttps://www.rand.org/pubs/papers/P2011.html1960-01-01T00:00:00Z1960-01-01T00:00:00ZAn application of the functional-equation technique of dynamic programming as a guide in the formulation and in the analytical and numerical treatment of chemical-engineering problems that involve multistage decision processes. Deterministic, stochas...A discussion of several concepts used in the optimization of control systems by dynamic programming.F. T. Smithhttps://www.rand.org/pubs/papers/P1665.html1959-01-01T00:00:00Z1959-01-01T00:00:00ZThe application of dynamic-programming techniques to the optimization of control systems. The concepts of the state of a controlled element and the transition matrix are used to describe the behavior of the controlled element. The paper discusses var...General Systems Approaches to Telecommunication Optimization.Robert E. Kalaba; M. L. Juncosahttps://www.rand.org/pubs/papers/P0964.html1957-01-01T00:00:00Z1957-01-01T00:00:00ZAn application of linear and dynamic programming to solve numerous communication system problems. Treatments for communication system extension problems and for equipment replacement policies are given, and various generalizations are indicated....Optimization in Dynamic Allocation Problems by a Modified Calculus of Variations TechniqueA. S. Mengelhttps://www.rand.org/pubs/research_memoranda/RM1379.html1954-01-01T00:00:00Z1954-01-01T00:00:00ZA direct proof that modified Euler equations solve linear-type problems that can not be optimized by the classical calculus of variations technique.