Explores the problems with the linear programming (LP) model used by Lee, Brown and Lovejoy in their paper which compared the mean-variance and stochastic efficiency criteria as predictors of the adoption of reduced t...
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Explores the problems with the linear programming (LP) model used by Lee, Brown and Lovejoy in their paper which compared the mean-variance and stochastic efficiency criteria as predictors of the adoption of reduced tillage. Difficulties with using a single-period LP model when farmers are making longer-term decisions; Integration of production and investment decisions over the planning horizon; Information on a multiperiod LP model as an alternative to the proposed LP model.
This paper gives a brief description of recent O.R. activity in China. It consists of four parts: mathematical programming; queueing theory and Markov decision processes; reliability theory; simulation. Emphasis is pl...
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This paper gives a brief description of recent O.R. activity in China. It consists of four parts: mathematical programming; queueing theory and Markov decision processes; reliability theory; simulation. Emphasis is placed on the current situation of practical O.R.
The present work deals with the usual stationary decision model of dynamic programming. The imposed convergence condition on the expected total rewards is so general that both the negative (unbounded) case and the pos...
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The present work deals with the usual stationary decision model of dynamic programming. The imposed convergence condition on the expected total rewards is so general that both the negative (unbounded) case and the positive (unbounded) case are included. However, the gambling model studied by Dubins and Savage is not covered by the present model. In addition to the convergence condition, a continuity and compactness condition is imposed. The main result states that the supremum of the expected total rewards under all stationary policies is equal to the supremum under all (possibly randomized and non-Markovian) policies.
This paper examines the problem of capital budgeting in the area of highway maintenance. Emphasis is placed on specific, real-world user concerns relating to standard capital budgeting models, and suggestions are made...
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This paper examines the problem of capital budgeting in the area of highway maintenance. Emphasis is placed on specific, real-world user concerns relating to standard capital budgeting models, and suggestions are made for improving planning in this area. A two-phase approach to capital budgeting is suggested as a mechanism for resolving some of these concerns. In phase 1 a financial planning model is used as a means of determining appropriate budget levels. In phase 2 a goal programming model for achieving desired levels of service is given. A brief description is given of such a two-phase system currently being implemented in a Canadian transport ministry.
Certain multistage decision problems that arise frequently in operations management planning and control allow a natural formulation as multistage stochastic programs. In job shop scheduling, for example, the first st...
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Certain multistage decision problems that arise frequently in operations management planning and control allow a natural formulation as multistage stochastic programs. In job shop scheduling, for example, the first stage could correspond to the acquisition of resources subject to probabilistic information about the jobs to be processed, and the second stage to the actual allocation of the resources to the jobs given deterministic information about their processing requirements. For two simple versions of this two-stage hierarchical scheduling problem, we describe heuristic solution methods and show that their performance is asymptotically optimal both in expectation and in probability.
Weak conditions are presented for approximating dynamic programming models. For a sequence of these models, continuous convergence of the sequence of associated optimal value functions is obtained under the condition ...
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Weak conditions are presented for approximating dynamic programming models. For a sequence of these models, continuous convergence of the sequence of associated optimal value functions is obtained under the condition that state and action space converge in the sense of Kuratowski, and that the mappings of admissible actions as well as the transition law, the discount factors and the reward functions converge continuously. Further a relation for the associated sets of optimal actions is given. The analysis is based on results about convergence preserving properties of supremum value functions and integrals. The approximation results are extended to so-called upper-semi-continuous convergent sequences and are related to discretization procedures by using projections.
A chance-constrained formulation is presented for a zero-one goal programming problem whose coefficients in the technological matrix are stochastic. The model is presented with a numerical example. A capital budgeting...
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A chance-constrained formulation is presented for a zero-one goal programming problem whose coefficients in the technological matrix are stochastic. The model is presented with a numerical example. A capital budgeting problem is taken for illustration.
This paper studies a deterministic dynamic programming model of fractional flows in an n-sector system, characterizing its solutions under general conditions, and developing algorithms for their computation. The calcu...
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This paper studies a deterministic dynamic programming model of fractional flows in an n-sector system, characterizing its solutions under general conditions, and developing algorithms for their computation. The calculations that the latter entail are not much more difficult than those needed for an n-state Markovian decision process (in certain restrictive cases, the model is "isomorphic" to an n-state MDP). Some of our results extend to a stochastic model as a "certainty equivalence." Applications include a maintenance/replacement/sales model, a manpower retention model that extends Flynn [8], [9], Grinold-Stanford [19] and Stanford [26], and a constrained version of Pliska's [25] branching model.
An abstract model of a processor is presented informally. The model can be used by itself to abstractly describe algorithms, or with a direct implementation to write and run programs, or as the foundation of a program...
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An abstract model of a processor is presented informally. The model can be used by itself to abstractly describe algorithms, or with a direct implementation to write and run programs, or as the foundation of a programming language. In the last case, a translator allows higher level descriptions of algorithms for the model.
Comments on a study which proposed a macromodel for the aggregation of programming models. Aggregation of von Thunen's model; Comparison of the macromodel with the macromodel proposed by Richard Day to consolidate...
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Comments on a study which proposed a macromodel for the aggregation of programming models. Aggregation of von Thunen's model; Comparison of the macromodel with the macromodel proposed by Richard Day to consolidate linear programs.
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