This paper responds to the Artificial Intelligence Design Challenge at the 1987 AIAA Guidance, Navigation, and Control Conference. It describes a computer program that solves a variation of the classical traveling sal...
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This paper responds to the Artificial Intelligence Design Challenge at the 1987 AIAA Guidance, Navigation, and Control Conference. It describes a computer program that solves a variation of the classical traveling salesman problem that is representative of problems encountered in complex guidance and control systems. The problem is to find a tour connecting some or all of 11 cities that maximizes the total value of the cities visited while meeting a travel budget constraint. The solution procedure used was to construct several candidate tours using a variety of approaches, then adjust the highest-value tour found by solving the traveling salesman problem to find the optimal city ordering. An efficient bounding procedure was used to reduce the number of computations required to evaluate the stochastic budget constraint. The program consistently produced in a small amount of time the best answers known on 25 data sets designed to test the program's robustness.
The Artificial Intelligence Design Challenge was an attempt to stimulate interest in a common problem involving the application of artificial intelligence technology to problems likely to be encountered in planning, s...
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The Artificial Intelligence Design Challenge was an attempt to stimulate interest in a common problem involving the application of artificial intelligence technology to problems likely to be encountered in planning, scheduling, and battle management. These problems are characterized by high combinatorial complexity, uncertainty, constraints, and, in some cases, requirements for real-time performance on finite-speed processors. Participants in the design challenge submitted competing, alternative approaches, implemented in computer code executable on desktop microcomputers, for assessment and relative evaluation over a range of problems. The range of problems was generated by variation of an input data file at the time of contest judging. The participants were given a priori knowledge of only the range of data variations, and not the specific details. In this manner, robustness to problem variations was evaluated, as was normalized performance of competing algorithms and implementations.
This paper presents a branch-and-boundalgorithm for minimizing the sum of a convex function in x, a convex function in y and a bilinear term in x and y over a closed set. Such an objective function is called biconvex...
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This paper presents a branch-and-boundalgorithm for minimizing the sum of a convex function in x, a convex function in y and a bilinear term in x and y over a closed set. Such an objective function is called biconvex with biconcave functions similarly defined. The feasible region of this model permits joint constraints in x and y to be expressed. The bilinear programming problem becomes a special case of the problem addressed in this paper. We prove that the minimum of a biconcave function over a nonempty compact set occurs at a boundary point of the set and not necessarily an extreme point. The algorithm is proven to converge to a global solution of the nonconvex program. We discuss extensions of the general model and computational experience in solving jointly constrained bilinear programs, for which the algorithm has been implemented.
In this article we develop a bounding procedure which is applied in an algorithm for determining the number of back-up components to include in a series system. Operating only when original units fail, back-up compone...
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In this article we develop a bounding procedure which is applied in an algorithm for determining the number of back-up components to include in a series system. Operating only when original units fail, back-up components increase system reliability. They also add weight, take up space, and cost money. Maximizing the reliability of nuclear power plants, ships, aircraft, life support systems and electronic instruments leads to this class of resource allocation problem. Because the procedure requires only that the rate of failure of individual components remains constant or increases with time, the algorithm can accommodate a wide variety of failure probability distributions. In applications, the failure probability for various types of components might belong to different families and this can be readily handled by the algorithm presented.
A branch and bound method to minimize the width of the control memory of microprogrammed processors is given. Although it is exponential in the worst case, it appears much more effective than previous enumerative solu...
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ABSTRACT: This paper describes a mathematical model, an algorithm and a computer program that were specially developed to study the problem of a water quality management system undergoing a rapidly increasing environm...
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SUMMARY: A very simple algorithm for obtaining maximum likelihood rankings of k objects which have been compared pairwise is presented. After some preliminary calculations, only addition and subtraction are required s...
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ABSTRACT. Individuals and organizations concerned with the expansion of the facilities of a river basin (such as a river basin authority) need to determine optimal strategies of operation and capital investment. They ...
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The study of the optimal expansion of existing water resources systems is of continuing importance because of the rising demand and limited supply of water in many areas of the world, particularly in the southwestern ...
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