Stanford University Department of Operations Research
Overview
Works:  449 works in 502 publications in 1 language and 577 library holdings 

Genres:  Periodicals 
Roles:  Researcher 
Classifications:  H61.25, 620 
Publication Timeline
.
Most widely held works by
Stanford University
Energy transition strategies : a progress report by
Stanford University(
Book
)
2 editions published in 1979 in English and held by 9 WorldCat member libraries worldwide
2 editions published in 1979 in English and held by 9 WorldCat member libraries worldwide
ETAMACRO : a model of energyeconomy interactions by
Alan Sussmann Manne(
Book
)
1 edition published in 1977 in English and held by 7 WorldCat member libraries worldwide
1 edition published in 1977 in English and held by 7 WorldCat member libraries worldwide
ETAMACRO : a progress report(
Book
)
1 edition published in 1983 in English and held by 6 WorldCat member libraries worldwide
1 edition published in 1983 in English and held by 6 WorldCat member libraries worldwide
ETAMACRO, a user's guide : interim report by
Alan Sussmann Manne(
Book
)
1 edition published in 1981 in English and held by 6 WorldCat member libraries worldwide
1 edition published in 1981 in English and held by 6 WorldCat member libraries worldwide
Technical report by
Stanford University(
)
in English and held by 6 WorldCat member libraries worldwide
in English and held by 6 WorldCat member libraries worldwide
Multiple channel queues in heavy traffic by
Donald L Iglehart(
Book
)
2 editions published in 1969 in English and held by 4 WorldCat member libraries worldwide
The queueing system considered consist of r. independent arrival channels and s independent service channels. These systems are assumed to be in heavy traffic, that is, the traffic intensity is greater than or equal to 1. Functional laws of the iterated logarithm are obtained for the queue length, departure, load, and waiting time processes. As immediate corollaries, the ordinary laws of the iterated logarithm are obtained for these processes. Finally, as an application of the functional law of the iterated logarithm, a limit theorem is obtained for the fraction of time the queue length process is above a given function. (Author)
2 editions published in 1969 in English and held by 4 WorldCat member libraries worldwide
The queueing system considered consist of r. independent arrival channels and s independent service channels. These systems are assumed to be in heavy traffic, that is, the traffic intensity is greater than or equal to 1. Functional laws of the iterated logarithm are obtained for the queue length, departure, load, and waiting time processes. As immediate corollaries, the ordinary laws of the iterated logarithm are obtained for these processes. Finally, as an application of the functional law of the iterated logarithm, a limit theorem is obtained for the fraction of time the queue length process is above a given function. (Author)
Markov maintenance models with repair by
Yukio Hatoyama(
)
1 edition published in 1976 in English and held by 4 WorldCat member libraries worldwide
In this study discrete time finite state Markov maintenance models are investigated. In each model, a machine is assumed to be operating over time with its condition deteriorating as time goes on. The state of the machine is observed at the beginning of a period. An operating machine can be sent to a repair shop at this time, whereas a failed machine must be repaired. When a machine is being repaired, the number of time periods that it is unavailable is usually assumed to have a geometric distribution. A repaired machine becomes available in its best state. An operating cost is charged while a machine is operating, and material and labor costs are charged when it is being repaired. The objective is to find a policy which minimizes the total expected alphadiscounted cost or the longrung average cost. Special emphasis is being placed on finding sufficient conditions to assure that a control limit policy is optimal. The aforementioned model had only one machine in the system. Models with spare machines in the system are next studied. For these models a penalty cost is added when the system fails (only when all machines are inoperative). (Author)
1 edition published in 1976 in English and held by 4 WorldCat member libraries worldwide
In this study discrete time finite state Markov maintenance models are investigated. In each model, a machine is assumed to be operating over time with its condition deteriorating as time goes on. The state of the machine is observed at the beginning of a period. An operating machine can be sent to a repair shop at this time, whereas a failed machine must be repaired. When a machine is being repaired, the number of time periods that it is unavailable is usually assumed to have a geometric distribution. A repaired machine becomes available in its best state. An operating cost is charged while a machine is operating, and material and labor costs are charged when it is being repaired. The objective is to find a policy which minimizes the total expected alphadiscounted cost or the longrung average cost. Special emphasis is being placed on finding sufficient conditions to assure that a control limit policy is optimal. The aforementioned model had only one machine in the system. Models with spare machines in the system are next studied. For these models a penalty cost is added when the system fails (only when all machines are inoperative). (Author)
A compact inverse scheme applied to multicommodity network with resource constraints by
Steven F Maier(
Book
)
2 editions published in 1971 in English and held by 4 WorldCat member libraries worldwide
2 editions published in 1971 in English and held by 4 WorldCat member libraries worldwide
Design of a linear programming system for the Illiac IV by
Stanford University(
Book
)
1 edition published in 1976 in English and held by 3 WorldCat member libraries worldwide
This paper outlines a design for implementing a linear programming system on the ILLIAC IV computer. The central concern is to take advantage of the special features of the ILLIAC IV (64 parallel processing elements, large fast disk memory and relatively small fast core memory) and at the same time to take advantage of the sparsity of real largescale linear programs and the (mostly serial) methodology which has been developed to exploit this sparsity. This requires both the adaption of existing techniques to a parallel environment and the development of a new parallel techniques for efficient sparse matrix processing. It appears that this can be done successfully and that ILLIAC IV should be able to solve problems considerably larger than those which can be attempted on serial computers. (Author)
1 edition published in 1976 in English and held by 3 WorldCat member libraries worldwide
This paper outlines a design for implementing a linear programming system on the ILLIAC IV computer. The central concern is to take advantage of the special features of the ILLIAC IV (64 parallel processing elements, large fast disk memory and relatively small fast core memory) and at the same time to take advantage of the sparsity of real largescale linear programs and the (mostly serial) methodology which has been developed to exploit this sparsity. This requires both the adaption of existing techniques to a parallel environment and the development of a new parallel techniques for efficient sparse matrix processing. It appears that this can be done successfully and that ILLIAC IV should be able to solve problems considerably larger than those which can be attempted on serial computers. (Author)
Static decision models for queueing systems with nonlinear waiting costs by
Shaler Stidham(
Book
)
3 editions published in 1968 in English and held by 3 WorldCat member libraries worldwide
Some models for the optimal design of queueing systems are presented. In most models studied, the decision variables are the number of servers (c) and the mean rate (mu) at which each serves. The objective function is the steadystate total expected cost rate of operating the system, which is assumed to be the sum of a cost of operating the service mechanism and a cost due to customers waiting in the system. It is shown that a singleserver system is optimal for a wide class of arrival processes and servicetime distributions, a wide variety of service and waiting cost functions, and a wide variety of system structures and operating policies. The optimality of the singleserver system is first demonstrated for singlestation models with general arrival process and degenerate, exponential, or Erlang servicetime distribution, where the servicecost rate is proportional to both c and mu and the waitingcost rate is proportional to the number of customers in the system. Several generalizations of this model are presented. (Author)
3 editions published in 1968 in English and held by 3 WorldCat member libraries worldwide
Some models for the optimal design of queueing systems are presented. In most models studied, the decision variables are the number of servers (c) and the mean rate (mu) at which each serves. The objective function is the steadystate total expected cost rate of operating the system, which is assumed to be the sum of a cost of operating the service mechanism and a cost due to customers waiting in the system. It is shown that a singleserver system is optimal for a wide class of arrival processes and servicetime distributions, a wide variety of service and waiting cost functions, and a wide variety of system structures and operating policies. The optimality of the singleserver system is first demonstrated for singlestation models with general arrival process and degenerate, exponential, or Erlang servicetime distribution, where the servicecost rate is proportional to both c and mu and the waitingcost rate is proportional to the number of customers in the system. Several generalizations of this model are presented. (Author)
Computing equilibrium compositions of ideal chemical systems by
J. H Bigelow(
Book
)
1 edition published in 1970 in English and held by 3 WorldCat member libraries worldwide
Six iterative methods are given for solving the chemical equilibrium problem, four primal and two dual. In chemical terms, each composition produced by a primal method satisfies the massbalance laws while successive iterates more nearly satisfy the massaction laws. Dual methods do the reverse. Also presented are two formulations of the chemical equilibrium problem as a more general linearlogarithmic problem, and two methods for solving the general problem. Of the four resulting primal methods, two (the Linear methods) need not converge to an optimal solution. The other two (the Quadratic methods) if applied to an appropriately modified chemical equilibrium problem, will certainly converge
1 edition published in 1970 in English and held by 3 WorldCat member libraries worldwide
Six iterative methods are given for solving the chemical equilibrium problem, four primal and two dual. In chemical terms, each composition produced by a primal method satisfies the massbalance laws while successive iterates more nearly satisfy the massaction laws. Dual methods do the reverse. Also presented are two formulations of the chemical equilibrium problem as a more general linearlogarithmic problem, and two methods for solving the general problem. Of the four resulting primal methods, two (the Linear methods) need not converge to an optimal solution. The other two (the Quadratic methods) if applied to an appropriately modified chemical equilibrium problem, will certainly converge
Probabilistic lower bound for two stage stochastic programs by
Stanford University(
Book
)
2 editions published in 1995 in English and held by 1 WorldCat member library worldwide
In the framework of Benders decomposition for twostage stochastic linear programs, the authors estimate the coefficients and righthand sides of the cutting planes using Monte Carlo sampling. The authors present a new theory for estimating a lower bound for the optimal objective value and they compare (using various test problems whose true optimal value is known) the predicted versus the observed rate of coverage of the optimal objective by the lower bound confidence interval
2 editions published in 1995 in English and held by 1 WorldCat member library worldwide
In the framework of Benders decomposition for twostage stochastic linear programs, the authors estimate the coefficients and righthand sides of the cutting planes using Monte Carlo sampling. The authors present a new theory for estimating a lower bound for the optimal objective value and they compare (using various test problems whose true optimal value is known) the predicted versus the observed rate of coverage of the optimal objective by the lower bound confidence interval
New approaches to linear and nonlinear programming. Progress report, January 1, 1988December 31, 1988(
)
1 edition published in 1988 in English and held by 0 WorldCat member libraries worldwide
This report describes technical progress during the past twelve months on DOE Contract DEFG87ER25030 and requests support for the third year. The project involves study of the theoretical properties and computational performance of techniques that solve linear and nonlinear programs by means of nonlinear transformations. The group at the Systems Optimization Laboratory (SOL) were the first to recognize the connection between Karmarkar's projective method and the logarithmic barrier method. It is now generally recognized that essentially all interiorpoint methods for linear programming inspired by Karmarkar's method are closely related to application of Newton's method to a sequence of barrier functions. Each barrier function is defined from the objective function and a barrier term that is infinite along the boundary of the feasible region. As the weight on the barrier term is reduced to zero, the solution of the subproblem becomes closer to the solution of the original problem
1 edition published in 1988 in English and held by 0 WorldCat member libraries worldwide
This report describes technical progress during the past twelve months on DOE Contract DEFG87ER25030 and requests support for the third year. The project involves study of the theoretical properties and computational performance of techniques that solve linear and nonlinear programs by means of nonlinear transformations. The group at the Systems Optimization Laboratory (SOL) were the first to recognize the connection between Karmarkar's projective method and the logarithmic barrier method. It is now generally recognized that essentially all interiorpoint methods for linear programming inspired by Karmarkar's method are closely related to application of Newton's method to a sequence of barrier functions. Each barrier function is defined from the objective function and a barrier term that is infinite along the boundary of the feasible region. As the weight on the barrier term is reduced to zero, the solution of the subproblem becomes closer to the solution of the original problem
New approaches to linear and nonlinear programming. Progress report, April 15, 1992January 31, 1993(
)
1 edition published in 1993 in English and held by 0 WorldCat member libraries worldwide
This program involves study of theoretical properties and computational performance of algorithms that solve linear and nonlinear programs. Emphasis is placed on algorithms to solve large problems, especially in the energy area. E.g., the safe, efficient distribution of electricity and the identification of the state of an electrical network are both largescale nonlinearly constrained optimization problems. Other applications include optimal trajectory calculations and optimal structural design
1 edition published in 1993 in English and held by 0 WorldCat member libraries worldwide
This program involves study of theoretical properties and computational performance of algorithms that solve linear and nonlinear programs. Emphasis is placed on algorithms to solve large problems, especially in the energy area. E.g., the safe, efficient distribution of electricity and the identification of the state of an electrical network are both largescale nonlinearly constrained optimization problems. Other applications include optimal trajectory calculations and optimal structural design
New approaches to linear and nonlinear programming(
)
1 edition published in 1988 in English and held by 0 WorldCat member libraries worldwide
This report describes technical progress during the past twelve months on DOE Contract DEFG87ER25030 and requests support for the third year. The project involves study of the theoretical properties and computational performance of techniques that solve linear and nonlinear programs by means of nonlinear transformations. The group at the Systems Optimization Laboratory (SOL) were the first to recognize the connection between Karmarkar's projective method and the logarithmic barrier method. It is now generally recognized that essentially all interiorpoint methods for linear programming inspired by Karmarkar's method are closely related to application of Newton's method to a sequence of barrier functions. Each barrier function is defined from the objective function and a barrier term that is infinite along the boundary of the feasible region. As the weight on the barrier term is reduced to zero, the solution of the subproblem becomes closer to the solution of the original problem
1 edition published in 1988 in English and held by 0 WorldCat member libraries worldwide
This report describes technical progress during the past twelve months on DOE Contract DEFG87ER25030 and requests support for the third year. The project involves study of the theoretical properties and computational performance of techniques that solve linear and nonlinear programs by means of nonlinear transformations. The group at the Systems Optimization Laboratory (SOL) were the first to recognize the connection between Karmarkar's projective method and the logarithmic barrier method. It is now generally recognized that essentially all interiorpoint methods for linear programming inspired by Karmarkar's method are closely related to application of Newton's method to a sequence of barrier functions. Each barrier function is defined from the objective function and a barrier term that is infinite along the boundary of the feasible region. As the weight on the barrier term is reduced to zero, the solution of the subproblem becomes closer to the solution of the original problem
New approaches to linear and nonlinear programming. Progress report, April 15, 1993February 28, 1994(
)
1 edition published in 1994 in English and held by 0 WorldCat member libraries worldwide
The project involves study of theoretical properties and computational performance of algorithms that solve linear and nonlinear programs, with emphasis on solving large problems, which is important in the energy area. For example, the safe and efficient distribution of electricity and identification of the state of an electrical network are largescale nonlinearly constrained optimization problems. Other application areas involved include optimal trajectory calculations and optimal structural design
1 edition published in 1994 in English and held by 0 WorldCat member libraries worldwide
The project involves study of theoretical properties and computational performance of algorithms that solve linear and nonlinear programs, with emphasis on solving large problems, which is important in the energy area. For example, the safe and efficient distribution of electricity and identification of the state of an electrical network are largescale nonlinearly constrained optimization problems. Other application areas involved include optimal trajectory calculations and optimal structural design
New approaches to linear and nonlinear programming. Final technical report, January 1, 1987December 31, 1989(
)
1 edition published in 1990 in English and held by 0 WorldCat member libraries worldwide
During the last twelve months, research has concentrated on barrier function methods for linear programming (LP) and quadratic programming (QP). Some groundwork for the application of barrier methods to nonlinearly constrained problems has also begun. In our previous progress report we drew attention to the difficulty of developing robust implementations of barrier methods for LP. We have continued to refine both the primal algorithm and the dual algorithm. We still do not claim that the barrier algorithms are as robust as the simplex method; however, the dual algorithm has solved all the problems in our extensive test set. We have also gained some experience with using the algorithms to solve aircrew scheduling problems
1 edition published in 1990 in English and held by 0 WorldCat member libraries worldwide
During the last twelve months, research has concentrated on barrier function methods for linear programming (LP) and quadratic programming (QP). Some groundwork for the application of barrier methods to nonlinearly constrained problems has also begun. In our previous progress report we drew attention to the difficulty of developing robust implementations of barrier methods for LP. We have continued to refine both the primal algorithm and the dual algorithm. We still do not claim that the barrier algorithms are as robust as the simplex method; however, the dual algorithm has solved all the problems in our extensive test set. We have also gained some experience with using the algorithms to solve aircrew scheduling problems
Solving linear programs under uncertainty, using decomposition, importance sampling and parallel processors. Progress report(
)
1 edition published in 1994 in English and held by 0 WorldCat member libraries worldwide
Planning under uncertainty is a fundamental problem of decision science where solution could advance man's ability to plan, schedule, design, and control complex situations. Goal is to develop efficient methods for solving an important class of planning problems, namely linear programs whose parameters (coefficients, right hand sides) are not known with certainty. The research concentrated on theoretical tasks of decomposition and importance sampling techniques, implementation, and software development issues and on applications. Research is continuing on use of parallel processors for solving stochastic programs
1 edition published in 1994 in English and held by 0 WorldCat member libraries worldwide
Planning under uncertainty is a fundamental problem of decision science where solution could advance man's ability to plan, schedule, design, and control complex situations. Goal is to develop efficient methods for solving an important class of planning problems, namely linear programs whose parameters (coefficients, right hand sides) are not known with certainty. The research concentrated on theoretical tasks of decomposition and importance sampling techniques, implementation, and software development issues and on applications. Research is continuing on use of parallel processors for solving stochastic programs
New approaches to linear and nonlinear programming(
)
1 edition published in 1993 in English and held by 0 WorldCat member libraries worldwide
This program involves study of theoretical properties and computational performance of algorithms that solve linear and nonlinear programs. Emphasis is placed on algorithms to solve large problems, especially in the energy area. E.g., the safe, efficient distribution of electricity and the identification of the state of an electrical network are both largescale nonlinearly constrained optimization problems. Other applications include optimal trajectory calculations and optimal structural design
1 edition published in 1993 in English and held by 0 WorldCat member libraries worldwide
This program involves study of theoretical properties and computational performance of algorithms that solve linear and nonlinear programs. Emphasis is placed on algorithms to solve large problems, especially in the energy area. E.g., the safe, efficient distribution of electricity and the identification of the state of an electrical network are both largescale nonlinearly constrained optimization problems. Other applications include optimal trajectory calculations and optimal structural design
New approaches to linear and nonlinear programming(
)
1 edition published in 1990 in English and held by 0 WorldCat member libraries worldwide
During the last twelve months, research has concentrated on barrier function methods for linear programming (LP) and quadratic programming (QP). Some groundwork for the application of barrier methods to nonlinearly constrained problems has also begun. In our previous progress report we drew attention to the difficulty of developing robust implementations of barrier methods for LP. We have continued to refine both the primal algorithm and the dual algorithm. We still do not claim that the barrier algorithms are as robust as the simplex method; however, the dual algorithm has solved all the problems in our extensive test set. We have also gained some experience with using the algorithms to solve aircrew scheduling problems
1 edition published in 1990 in English and held by 0 WorldCat member libraries worldwide
During the last twelve months, research has concentrated on barrier function methods for linear programming (LP) and quadratic programming (QP). Some groundwork for the application of barrier methods to nonlinearly constrained problems has also begun. In our previous progress report we drew attention to the difficulty of developing robust implementations of barrier methods for LP. We have continued to refine both the primal algorithm and the dual algorithm. We still do not claim that the barrier algorithms are as robust as the simplex method; however, the dual algorithm has solved all the problems in our extensive test set. We have also gained some experience with using the algorithms to solve aircrew scheduling problems
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Related Identities
 United States Office of Naval Research
 National Science Foundation (U.S.)
 United States Department of Energy Sponsor
 Electric Power Research Institute
 Dantzig, George B. Author
 Cottle, Richard W. Author
 United States Energy Research and Development Administration
 United States Army Research Office
 Stanford University Department of Statistics
 United States Department of Energy Office of Scientific and Technical Information Distributor
Associated Subjects
Breeder reactors Chemical equilibriumMathematics Civil engineeringResearch Computers Computer science Computer scienceMathematics ComputersResearch Computer systems Economic history Economics Education Electric power Electric utilities Electronic data processing Electronic digital computers Electronics ElectronicsResearch ElectronicsSocieties, etc Energy developmentEconomic aspects Energy industriesEconomic aspects Energy policy Faulttolerant computing Integrated circuits Linear programming MachineryMaintenance and repairMathematical models MacroeconomicsMathematical models Markov processes Mathematical optimization Mathematical statistics Mathematics Medical statistics Network analysis (Planning) Operations research Physics Power resourcesEconomic aspects Power resourcesMathematical models Power resourcesSupply and demand Punched card systems Queuing theory Radio waves Semiconductors Social sciencesMathematical models Social sciencesMathematics Solids Solid state electronics Statistical decisionMathematical models System analysis Traffic engineeringMathematical models Traffic flowMathematical models United States
Alternative Names
Stanford University. Program in Operations Research
Department of Operations Research
Stanford University. Dept. of Operations Research
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