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193
Lazy Satisfiability Modulo Theories
 JOURNAL ON SATISFIABILITY, BOOLEAN MODELING AND COMPUTATION 3 (2007) 141Â224
, 2007
"... Satisfiability Modulo Theories (SMT) is the problem of deciding the satisfiability of a firstorder formula with respect to some decidable firstorder theory T (SMT (T)). These problems are typically not handled adequately by standard automated theorem provers. SMT is being recognized as increasingl ..."
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Cited by 97 (38 self)
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Satisfiability Modulo Theories (SMT) is the problem of deciding the satisfiability of a firstorder formula with respect to some decidable firstorder theory T (SMT (T)). These problems are typically not handled adequately by standard automated theorem provers. SMT is being recognized as increasingly important due to its applications in many domains in different communities, in particular in formal verification. An amount of papers with novel and very efficient techniques for SMT has been published in the last years, and some very efficient SMT tools are now available. Typical SMT (T) problems require testing the satisfiability of formulas which are Boolean combinations of atomic propositions and atomic expressions in T, so that heavy Boolean reasoning must be efficiently combined with expressive theoryspecific reasoning. The dominating approach to SMT (T), called lazy approach, is based on the integration of a SAT solver and of a decision procedure able to handle sets of atomic constraints in T (Tsolver), handling respectively the Boolean and the theoryspecific components of reasoning. Unfortunately, neither the problem of building an efficient SMT solver, nor even that
Global inference for sentence compression: An integer linear programming approach
 Journal of Artificial Intelligence Research (JAIR
, 2008
"... Sentence compression holds promise for many applications ranging from summarization to subtitle generation. Our work views sentence compression as an optimization problem and uses integer linear programming (ILP) to infer globally optimal compressions in the presence of linguistically motivated cons ..."
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Cited by 73 (7 self)
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Sentence compression holds promise for many applications ranging from summarization to subtitle generation. Our work views sentence compression as an optimization problem and uses integer linear programming (ILP) to infer globally optimal compressions in the presence of linguistically motivated constraints. We show how previous formulations of sentence compression can be recast as ILPs and extend these models with novel global constraints. Experimental results on written and spoken texts demonstrate improvements over stateoftheart models. 1.
Numerical experience with lower bounds for MIQP branchandbound
, 1995
"... The solution of convex Mixed Integer Quadratic Programming (MIQP) problems with a general branchandbound framework is considered. It is shown how lower bounds can be computed efficiently during the branchandbound process. Improved lower bounds such as the ones derived in this paper can reduc ..."
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Cited by 54 (0 self)
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The solution of convex Mixed Integer Quadratic Programming (MIQP) problems with a general branchandbound framework is considered. It is shown how lower bounds can be computed efficiently during the branchandbound process. Improved lower bounds such as the ones derived in this paper can reduce the number of QP problems that have to be solved. The branchandbound approach is also shown to be superior to other approaches to solving MIQP problems. Numerical experience is presented which supports these conclusions. Key words : Integer Programming, Mixed Integer Quadratic Programming, BranchandBound AMS subject classification: 90C10, 90C11, 90C20 1 Introduction One of the most successful methods for solving mixedinteger nonlinear problems is branchandbound. Land and Doig [16] first introduced a branchandbound algorithm for the travelling salesman problem. Dakin [3] introduced the now common branching dichotomy and was the first to realize that it is possible to so...
A Computational Study of Search Strategies for Mixed Integer Programming
 INFORMS Journal on Computing
, 1997
"... The branch and bound procedure for solving mixed integer programming (MIP) problems using linear programming relaxations has been used with great success for decades. Over the years, a variety of researchers have studied ways of making the basic algorithm more effective. Breakthroughs in the fiel ..."
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Cited by 51 (6 self)
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The branch and bound procedure for solving mixed integer programming (MIP) problems using linear programming relaxations has been used with great success for decades. Over the years, a variety of researchers have studied ways of making the basic algorithm more effective. Breakthroughs in the fields of computer hardware, computer software, and mathematics have led to increasing success at solving larger and larger MIP instances. The goal of this paper is to survey many of the results regarding branch and bound search strategies and evaluate them again in light of the other advances that have taken place over the years. In addition, novel search strategies are presented and shown to often perform better than those currently used in practice. October 1997 The effectiveness of the branch and bound procedure for solving mixed integer programming (MIP) problems using linear programming relaxations is well documented. After the introduction of this procedure in the 1960's [26] [10]...
EVBDDbased algorithms for integer linear programming, spectral transformation, and function decomposition
 IEEE TRANSACTIONS ON COMPUTERAIDED DESIGN OF INTEGRATED CIRCUITS AND SYSTEMS
, 1994
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MIP: Theory And Practice  Closing The Gap
 System Modelling and Optimization: Methods, Theory, and Applications
, 2000
"... this paper, now include cuttingplane capabilities as well as other ideas from the backlog of accumulated theory. As suggested by the title of this paper, the gap between theory and practice is indeed closing ..."
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Cited by 45 (1 self)
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this paper, now include cuttingplane capabilities as well as other ideas from the backlog of accumulated theory. As suggested by the title of this paper, the gap between theory and practice is indeed closing
Neural Networks for Combinatorial Optimization: A Review of More Than a Decade of Research
, 1999
"... This article briefly summarizes the work that has been done and presents the current standing of neural networks for combinatorial optimization by considering each of the major classes of combinatorial optimization problems. Areas which have not yet been studied are identified for future research. ..."
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Cited by 34 (0 self)
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This article briefly summarizes the work that has been done and presents the current standing of neural networks for combinatorial optimization by considering each of the major classes of combinatorial optimization problems. Areas which have not yet been studied are identified for future research.
Overlapping coalition formation for efficient data fusion in multisensor networks
 in Proceedings of the 21st AAAI
, 2006
"... This paper develops new algorithms for coalition formation within multisensor networks tasked with performing widearea surveillance. Specifically, we cast this application as an instance of coalition formation, with overlapping coalitions. We show that within this application area subadditive co ..."
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Cited by 32 (12 self)
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This paper develops new algorithms for coalition formation within multisensor networks tasked with performing widearea surveillance. Specifically, we cast this application as an instance of coalition formation, with overlapping coalitions. We show that within this application area subadditive coalition valuations are typical, and we thus use this structural property of the problem to derive two novel algorithms (an approximate greedy one that operates in polynomial time and has a calculated bound to the optimum, and an optimal branchandbound one) to find the optimal coalition structure in this instance. We empirically evaluate the performance of these algorithms within a generic model of a multisensor network performing wide area surveillance. These results show that the polynomial algorithm typically generated solutions much closer to the optimal than the theoretical bound, and prove the effectiveness of our pruning procedure.
Integrating SQP and branchandbound for Mixed Integer Nonlinear Programming
 Computational Optimization and Applications
, 1998
"... This paper considers the solution of Mixed Integer Nonlinear Programming (MINLP) problems. Classical methods for the solution of MINLP problems decompose the problem by separating the nonlinear part from the integer part. This approach is largely due to the existence of packaged software for solving ..."
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Cited by 27 (0 self)
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This paper considers the solution of Mixed Integer Nonlinear Programming (MINLP) problems. Classical methods for the solution of MINLP problems decompose the problem by separating the nonlinear part from the integer part. This approach is largely due to the existence of packaged software for solving Nonlinear Programming (NLP) and Mixed Integer Linear Programming problems. In contrast, an integrated approach to solving MINLP problems is considered here. This new algorithm is based on branchandbound, but does not require the NLP problem at each node to be solved to optimality. Instead, branching is allowed after each iteration of the NLP solver. In this way, the nonlinear part of the MINLP problem is solved whilst searching the tree. The nonlinear solver that is considered in this paper is a Sequential Quadratic Programming solver. A numerical comparison of the new method with nonlinear branchandbound is presented and a factor of about 3 improvement over branchandbound is observed...
TSP cuts which do not conform to the template paradigm
 IN COMPUTATIONAL COMBINATORIAL OPTIMIZATION
, 2001
"... The first computer implementation of the DantzigFulkersonJohnson cuttingplane method for solving the traveling salesman problem, written by Martin, used subtour inequalities as well as cutting planes of Gomory’s type. The practice of looking for and using cuts that match prescribed templates in c ..."
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Cited by 27 (1 self)
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The first computer implementation of the DantzigFulkersonJohnson cuttingplane method for solving the traveling salesman problem, written by Martin, used subtour inequalities as well as cutting planes of Gomory’s type. The practice of looking for and using cuts that match prescribed templates in conjunction with Gomory cuts was continued in computer codes of Miliotis, Land, and Fleischmann. Grötschel, Padberg, and Hong advocated a different policy, where the template paradigm is the only source of cuts; furthermore, they argued for drawing the templates exclusively from the set of linear inequalities that induce facets of the TSP polytope. These policies were adopted in the work of Crowder and Padberg, in the work of Grötschel and Holland, and in the work of Padberg and Rinaldi; their computer codes produced the most impressive computational TSP successes of the nineteen eighties. Eventually, the template paradigm became the standard frame of reference for cutting planes in the TSP. The purpose of this paper is to describe a technique