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Complexity and Approximation
, 1999
"... Abstract. In this survey the following model is considered. We assume that an instance I of a computationally hard optimization problem has been solved and that we know the optimum solution of such instance. Then a new instance I ′ is proposed, obtained by means of a slight perturbation of instance ..."
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Cited by 174 (1 self)
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Abstract. In this survey the following model is considered. We assume that an instance I of a computationally hard optimization problem has been solved and that we know the optimum solution of such instance. Then a new instance I ′ is proposed, obtained by means of a slight perturbation of instance I. How can we exploit the knowledge we have on the solution of instance I to compute a (approximate) solution of instance I ′ in an efficient way? This computation model is called reoptimization and is of practical interest in various circumstances. In this article we first discuss what kind of performance we can expect for specific classes of problems and then we present some classical optimization problems (i.e. Max Knapsack, Min Steiner Tree, Scheduling) in which this approach has been fruitfully applied. Subsequently, we address vehicle routing problems and we show how the reoptimization approach can be used to obtain good approximate solution in an efficient way for some of these problems. 1
Algorithms for the Satisfiability (SAT) Problem: A Survey
 DIMACS Series in Discrete Mathematics and Theoretical Computer Science
, 1996
"... . The satisfiability (SAT) problem is a core problem in mathematical logic and computing theory. In practice, SAT is fundamental in solving many problems in automated reasoning, computeraided design, computeraided manufacturing, machine vision, database, robotics, integrated circuit design, compute ..."
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Cited by 124 (3 self)
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. The satisfiability (SAT) problem is a core problem in mathematical logic and computing theory. In practice, SAT is fundamental in solving many problems in automated reasoning, computeraided design, computeraided manufacturing, machine vision, database, robotics, integrated circuit design, computer architecture design, and computer network design. Traditional methods treat SAT as a discrete, constrained decision problem. In recent years, many optimization methods, parallel algorithms, and practical techniques have been developed for solving SAT. In this survey, we present a general framework (an algorithm space) that integrates existing SAT algorithms into a unified perspective. We describe sequential and parallel SAT algorithms including variable splitting, resolution, local search, global optimization, mathematical programming, and practical SAT algorithms. We give performance evaluation of some existing SAT algorithms. Finally, we provide a set of practical applications of the sat...
Planning by Rewriting
 Journal of Artificial Intelligence Research
, 2001
"... Domainindependent planning is a hard combinatorial problem. Taking into account plan quality makes the task even more difficult. This article introduces Planning by Rewriting (PbR), a new paradigm for efficient highquality domainindependent planning. PbR exploits declarative planrewriting rules ..."
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Cited by 34 (4 self)
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Domainindependent planning is a hard combinatorial problem. Taking into account plan quality makes the task even more difficult. This article introduces Planning by Rewriting (PbR), a new paradigm for efficient highquality domainindependent planning. PbR exploits declarative planrewriting rules and efficient local search techniques to transform an easytogenerate, but possibly suboptimal, initial plan into a highquality plan. In addition to addressing the issues of planning efficiency and plan quality, this framework offers a new anytime planning algorithm. We have implemented this planner and applied it to several existing domains. The experimental results show that the PbR approach provides significant savings in planning effort while generating highquality plans.
LatticeBased Search Strategies For Large Vocabulary Speech Recognition
, 1995
"... The design of search algorithms is an important issue in recognition, particularly for very large vocabulary, continuous speech. It is an especially crucial problem when computationally expensive knowledge sources are used in the system, as is necessary to achieve high accuracy. Recently, multipass ..."
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Cited by 11 (1 self)
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The design of search algorithms is an important issue in recognition, particularly for very large vocabulary, continuous speech. It is an especially crucial problem when computationally expensive knowledge sources are used in the system, as is necessary to achieve high accuracy. Recently, multipass search strategies have been used as a means of applying inexpensive knowledge sources early on to prune the search space for subsequent passes using more expensive knowledge sources. Three multipass search algorithms are investigated in this thesis work: the Nbest search algorithm, a lattice dynamic programming search algorithm and a lattice local search algorithm. Both the lattice dynamic programming and lattice local search algorithms are shown to achieve comparable performance to the Nbest search algorithm while running as much as 10 times faster on a 20,000 word vocabulary task. The lattice local search algorithm is also shown to have the additional advantage over the lattice dynamic programming search algorithm of allowing sentencelevel knowledge sources to be incorporated into the search.
Local Search: Is bruteforce avoidable?
"... Many local search algorithms are based on searching in the kexchange neighborhood. This is the set of solutions that can be obtained from the current solution by exchanging at most k elements. As a rule of thumb, the larger k is, the better are the chances of finding an improved solution. However, ..."
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Cited by 8 (0 self)
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Many local search algorithms are based on searching in the kexchange neighborhood. This is the set of solutions that can be obtained from the current solution by exchanging at most k elements. As a rule of thumb, the larger k is, the better are the chances of finding an improved solution. However, for inputs of size n, anaïve bruteforce search of the kexchange neighborhood requires nO(k) time, which is not practical even for very small values of k. We show that for several classes of sparse graphs, like planar graphs, graphs of bounded vertex degree and graphs excluding some fixed graph as a minor, an improved solution in the kexchange neighborhood for many problems can be found much more efficiently. Our algorithms run in time O(τ(k) · nc), where τ is a function depending on k only and c is a constant independent of k. We demonstrate the applicability of this approach on different problems like rCENTER,
LOCAL OPTIMIZATION FOR GLOBAL ALIGNMENT OF PROTEIN INTERACTION NETWORKS
"... We propose a novel algorithm, PISwap, for computing global pairwise alignments of protein interaction networks, based on a local optimization heuristic that has previously demonstrated its effectiveness for a variety of other NPhard problems, such as the Traveling Salesman Problem. Our algorithm be ..."
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Cited by 5 (0 self)
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We propose a novel algorithm, PISwap, for computing global pairwise alignments of protein interaction networks, based on a local optimization heuristic that has previously demonstrated its effectiveness for a variety of other NPhard problems, such as the Traveling Salesman Problem. Our algorithm begins with a sequencebased network alignment and then iteratively adjusts the alignment by incorporating network structure information. It has a worstcase pseudopolynomial runningtime bound and is very efficient in practice. It is shown to produce improved alignments in several wellstudied cases. In addition, the flexible nature of this algorithm makes it suitable for different applications of network alignments. Finally, this algorithm can yield interesting insights into the evolutionary history of the compared species.
On the Relative Complexity of 15 Problems Related to 0/1Integer Programming
"... An integral part of combinatorial optimization and computational complexity consists of establishing relationships between different problems or different versions of the same problem. In this chapter, we bring together known and new, previously published and unpublished results, which establish th ..."
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Cited by 4 (1 self)
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An integral part of combinatorial optimization and computational complexity consists of establishing relationships between different problems or different versions of the same problem. In this chapter, we bring together known and new, previously published and unpublished results, which establish that 15 problems related to optimizing a linear function over a 0/1polytope are polynomialtime equivalent. This list of problems includes optimization and augmentation, testing optimality and primal separation, sensitivity analysis and inverse optimization, and several others.
Implementation of a Linear Time Algorithm for Certain Generalized Traveling Salesman Problems
 In Integer Programming and Combinatorial Optimization: Proc. 5th Int. IPCO Conference, LNCS 840
, 1996
"... This paper discusses an implementation of a dynamic programming approach to the traveling salesman problem that runs in time linear in the number of cities. Optimality can be guaranteed when precedence constraints of a certain type are present, and many problems involving time windows fall into this ..."
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Cited by 4 (0 self)
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This paper discusses an implementation of a dynamic programming approach to the traveling salesman problem that runs in time linear in the number of cities. Optimality can be guaranteed when precedence constraints of a certain type are present, and many problems involving time windows fall into this class. Perhaps the most interesting feature of the procedure is that an auxiliary structure is built before any particular problem instance is known, reducing the computational effort required to solve a given problem instance to a fraction of what it would be without such a structure. 1
Linear Time DynamicProgramming Algorithms for New Classes of Restricted TSPs: A Computational Study
, 2001
"... this paper we discuss an implementation of the dynamicprogramming algorithm for the general case when the integer k is replaced with cityspecific integers k(j), j = 1, . . . , n ..."
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Cited by 4 (0 self)
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this paper we discuss an implementation of the dynamicprogramming algorithm for the general case when the integer k is replaced with cityspecific integers k(j), j = 1, . . . , n
Effective Local and Guided Variable Neighbourhood Search Methods for the Asymmetric Travelling Salesman Problem
, 2001
"... In this paper we present effective new local and variable neighbourhood search heuristics for the asymmetric Travelling Salesman Problem. Our local search approach, HyperOpt, is inspired by a heuristic developed for a sequencing problem arising in the manufacture of printed circuit boards. In our ap ..."
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Cited by 3 (0 self)
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In this paper we present effective new local and variable neighbourhood search heuristics for the asymmetric Travelling Salesman Problem. Our local search approach, HyperOpt, is inspired by a heuristic developed for a sequencing problem arising in the manufacture of printed circuit boards. In our approach we embed an exact algorithm into a local search heuristic in order to exhaustively search promising regions of the solution space. We propose a hybrid of HyperOpt and 3opt which allows us to benefit from the advantages of both approaches and gain better tours overall. Using this hybrid within the Variable Neighbourhood Search (VNS) metaheuristic framework, as suggested by Hansen and Mladenovic, allows us to overcome local optima and create tours of very high quality. We introduce the notion of a "guided shake" within VNS and show that this yields a heuristic which is more effective than the random shakes proposed by Hansen and Mladenovic. The heuristics presented form a continuum from very fast ones which produce reasonable results to much slower ones which produce excellent results. All of the heuristics have proven capable of handling the sort of constraints which arise for real life problems, such as those in electronics assembly.