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Computational experience with an interior point algorithm on the satisfiability problem
 Annals of Operations Research
, 1990
"... We apply the zeroone integer programming algorithm described in Karmarkar [12] and Karmarkar, Resende and Ramakrishnan [13] to solve randomly generated instances of the satisfiability problem (SAT). The interior point algorithm is briefly reviewed and shown to be easily adapted to solve large insta ..."
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Cited by 43 (4 self)
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We apply the zeroone integer programming algorithm described in Karmarkar [12] and Karmarkar, Resende and Ramakrishnan [13] to solve randomly generated instances of the satisfiability problem (SAT). The interior point algorithm is briefly reviewed and shown to be easily adapted to solve large instances of SAT. Hundreds of instances of SAT (having from 100 to 1000 variables and 100 to 32,000 clauses) are randomly generated and solved. For comparison, we attempt to solve the problems via linear programming relaxation with MINOS.
A Continuous Approach to Inductive Inference
 Mathematical Programming
, 1992
"... In this paper we describe an interior point mathematical programming approach to inductive inference. We list several versions of this problem and study in detail the formulation based on hidden Boolean logic. We consider the problem of identifying a hidden Boolean function F : f0; 1g n ! f0; 1g ..."
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Cited by 38 (2 self)
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In this paper we describe an interior point mathematical programming approach to inductive inference. We list several versions of this problem and study in detail the formulation based on hidden Boolean logic. We consider the problem of identifying a hidden Boolean function F : f0; 1g n ! f0; 1g using outputs obtained by applying a limited number of random inputs to the hidden function. Given this inputoutput sample, we give a method to synthesize a Boolean function that describes the sample. We pose the Boolean Function Synthesis Problem as a particular type of Satisfiability Problem. The Satisfiability Problem is translated into an integer programming feasibility problem, that is solved with an interior point algorithm for integer programming. A similar integer programming implementation has been used in a previous study to solve randomly generated instances of the Satisfiability Problem. In this paper we introduce a new variant of this algorithm, where the Riemannian metric used...
INTERIOR POINT METHODS FOR COMBINATORIAL OPTIMIZATION
, 1995
"... Research on using interior point algorithms to solve combinatorial optimization and integer programming problems is surveyed. This paper discusses branch and cut methods for integer programming problems, a potential reduction method based on transforming an integer programming problem to an equivale ..."
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Cited by 14 (9 self)
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Research on using interior point algorithms to solve combinatorial optimization and integer programming problems is surveyed. This paper discusses branch and cut methods for integer programming problems, a potential reduction method based on transforming an integer programming problem to an equivalent nonconvex quadratic programming problem, interior point methods for solving network flow problems, and methods for solving multicommodity flow problems, including an interior point column generation algorithm.
Interior Point Methods For Global Optimization
 INTERIOR POINT METHODS OF MATHEMATICAL PROGRAMMING
, 1996
"... Interior point methods, originally invented in the context of linear programming, have found a much broader range of applications, including global optimization problems that arise in engineering, computer science, operations research, and other disciplines. This chapter overviews the conceptual bas ..."
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Cited by 4 (1 self)
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Interior point methods, originally invented in the context of linear programming, have found a much broader range of applications, including global optimization problems that arise in engineering, computer science, operations research, and other disciplines. This chapter overviews the conceptual basis and applications of interior point methods for some classes of global optimization problems.
Experimental analyses of the life span method for the quadratic assignment porblem
 The Institute of Statistical Mathematics Cooperative Research Report
, 1995
"... In this paper, we report an application of the life span method (LSM), a variant of tabu search introduced by the authors, to the quadratic assignment problem which has applications on facility location and backboard wiring, etc. We discuss how to adapt the LSM to the quadratic assignment problem an ..."
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Cited by 1 (1 self)
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In this paper, we report an application of the life span method (LSM), a variant of tabu search introduced by the authors, to the quadratic assignment problem which has applications on facility location and backboard wiring, etc. We discuss how to adapt the LSM to the quadratic assignment problem and compare the performance with previous heuristics. The main purpose of this paper is to perform experimental analyses composed of optimizing the various parameters and to estimate the performance not only in the best case but the average behavior. Key words: life span method, tabu search, combinatorial optimization, approximate algorithms, experimental analysis, quadratic assignment problem. 1