The Experts below are selected from a list of 31947 Experts worldwide ranked by ideXlab platform
Hubert Cardot - One of the best experts on this subject based on the ideXlab platform.
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Tabu Search model selection for SVM
International Journal of Neural Systems, 2008Co-Authors: Gilles Lebrun, Christophe Charrier, Olivier Lezoray, Hubert CardotAbstract:A model selection method based on Tabu Search is proposed to build support vector machines (binary decision functions) of reduced complexity and efficient generalization. The aim is to build a fast and efficient support vector machines classifier. A criterion is defined to evaluate the decision function quality which blends recognition rate and the complexity of a binary decision functions together. The selection of the simplification level by vector quantization, of a feature subset and of support vector machines hyperparameters are performed by Tabu Search method to optimize the defined decision function quality criterion in order to find a good sub-optimal model on tractable times.
Fred Glover - One of the best experts on this subject based on the ideXlab platform.
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Probabilistic GRASP-Tabu Search algorithms for the UBQP problem
Computers & Operations Research, 2013Co-Authors: Yang Wang, Fred Glover, Jin-kao HaoAbstract:This paper presents two algorithms combining GRASP and Tabu Search for solving the Unconstrained Binary Quadratic Programming (UBQP) problem. We first propose a simple GRASP-Tabu Search algorithm working with a single solution and then reinforce it by introducing a population management strategy. Both algorithms are based on a dedicated randomized greedy construction heuristic and a Tabu Search procedure. We show extensive computational results on two sets of 31 large random UBQP instances and one set of 54 structured instances derived from the MaxCut problem. Comparisons with state-of-the-art algorithms demonstrate the efficacy of our proposed algorithms in terms of both solution quality and computational efficiency. It is noteworthy that the reinforced GRASP-Tabu Search algorithm is able to improve the previous best known results for 19 MaxCut instances.
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Tabu Search and finite convergence
Discrete Applied Mathematics, 2002Co-Authors: Fred Glover, Saïd HanafiAbstract:Abstract We establish finite convergence for some Tabu Search algorithms based on recency memory or frequency memory, distinguishing between symmetric and asymmetric neighborhood structures. These are the first demonstrations of explicit bounds provided by such forms of memory, and their finiteness suggests an important distinction between these ideas and those underlying certain “probabilistic” procedures such as annealing. We also show how an associated reverse elimination memory can be used to create a new type of tree Search. Finally, we give designs for more efficient forms of convergent Tabu Search.
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Tabu Search andnite convergence
2002Co-Authors: Fred GloverAbstract:We establishnite convergence for some Tabu Search algorithms based on recency memory or frequency memory, distinguishing between symmetric and asymmetric neighborhood structures. These are therst demonstrations of explicit bounds provided by such forms of memory, and theirniteness suggests an important distinction between these ideas and those underlying certain "probabilistic" procedures such as annealing. We also show how an associated reverse elimination memory can be used to create a new type of tree Search. Finally, we give designs for more e5cient forms of convergent Tabu Search. ? 2002 Elsevier Science B.V. All rights reserved.
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fine tuning a Tabu Search algorithm with statistical tests
International Transactions in Operational Research, 1998Co-Authors: Jiefeng Xu, Steve Y Chiu, Fred GloverAbstract:Abstract Tabu Search is a metaheuristic that has proven to be very effective for solving various types ofcombinatorial optimization problems. To achieve the best results with a Tabu Search algorithm, significant benefits can sometimes be gained by determining preferred values for certain Search parameters such as Tabu tenures, move selection probabilities, the timing and structure of elite solution recovery for intensification, etc. In this paper, we present and implement some new ideas for fine-tuning a Tabu Search algorithm using statistical tests. Although the focus of this work is to improve a particular Tabu Search algorithm developed for solving a telecommunications network design problem, the implications are quite general. The same ideas and procedures can easily be adapted and applied to other Tabu Search algorithms as well.
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Tabu Search
1997Co-Authors: Fred Glover, Manuel LagunaAbstract:From the Publisher: This book explores the meta-heuristics approach called Tabu Search, which is dramatically changing our ability to solve a hostof problems that stretch over the realms of resource planning,telecommunications, VLSI design, financial analysis, scheduling, spaceplanning, energy distribution, molecular engineering, logistics,pattern classification, flexible manufacturing, waste management,mineral exploration, biomedical analysis, environmental conservationand scores of other problems. The major ideas of Tabu Search arepresented with examples that show their relevance to multipleapplications. Numerous illustrations and diagrams are used to clarifyprinciples that deserve emphasis, and that have not always been wellunderstood or applied. The book's goal is to provide ''hands-on' knowledge and insight alike, rather than to focus exclusively eitheron computational recipes or on abstract themes. This book is designedto be useful and accessible to reSearchers and practitioners inmanagement science, industrial engineering, economics, and computerscience. It can appropriately be used as a textbook in a masterscourse or in a doctoral seminar. Because of its emphasis on presentingideas through illustrations and diagrams, and on identifyingassociated practical applications, it can also be used as asupplementary text in upper division undergraduate courses. Finally, there are many more applications of Tabu Search than canpossibly be covered in a single book, and new ones are emerging everyday. The book's goal is to provide a grounding in the essential ideasof Tabu Search that will allow readers to create successfulapplications of their own. Along with the essentialideas,understanding of advanced issues is provided, enabling reSearchers togo beyond today's developments and create the methods of tomorrow.
Gilles Lebrun - One of the best experts on this subject based on the ideXlab platform.
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Tabu Search model selection for SVM
International Journal of Neural Systems, 2008Co-Authors: Gilles Lebrun, Christophe Charrier, Olivier Lezoray, Hubert CardotAbstract:A model selection method based on Tabu Search is proposed to build support vector machines (binary decision functions) of reduced complexity and efficient generalization. The aim is to build a fast and efficient support vector machines classifier. A criterion is defined to evaluate the decision function quality which blends recognition rate and the complexity of a binary decision functions together. The selection of the simplification level by vector quantization, of a feature subset and of support vector machines hyperparameters are performed by Tabu Search method to optimize the defined decision function quality criterion in order to find a good sub-optimal model on tractable times.
Hyun Woong Jin - One of the best experts on this subject based on the ideXlab platform.
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A Tabu-Search-based heuristic for clustering
Pattern Recognition, 2000Co-Authors: Chang Sup Sung, Hyun Woong JinAbstract:Abstract This paper considers a clustering problem where a given data set is partitioned into a certain number of natural and homogeneous subsets such that each subset is composed of elements similar to one another but different from those of any other subset. For the clustering problem, a heuristic algorithm is exploited by combining the Tabu Search heuristic with two complementary functional procedures, called packing and releasing procedures. The algorithm is numerically tested for its effectiveness in comparison with reference works including the Tabu Search algorithm, the K -means algorithm and the simulated annealing algorithm.
Gilbert Laporte - One of the best experts on this subject based on the ideXlab platform.
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A Tabu Search heuristic for ship routing and scheduling
Journal of the Operational Research Society, 2010Co-Authors: J E Korsvik, K Fagerholt, Gilbert LaporteAbstract:The purpose of this paper is to solve a planning problem faced by many shipping companies dealing with the transport of bulk products. These shipping companies are committed to carrying some contract cargoes and will try to derive additional revenue from optional spot cargoes. An efficient Tabu Search algorithm has been developed to ensure quick decision support for the planners. The solutions generated by the Tabu Search heuristic are compared with those produced by a previously published multi-start local Search heuristic. Computational results show that the Tabu Search heuristic yields optimal or near-optimal solutions to real-life instances within reasonable time. For large and tigthly constrained cases, the Tabu Search heuristic provides much better solutions than the multi-start local Search heuristic. A version of the Tabu Search heuristic will be integrated as an improved solver in a prototype decision support system used by several shipping companies.
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Iterated Tabu Search for the car sequencing problem
European Journal of Operational Research, 2008Co-Authors: Jean-françois Cordeau, Gilbert Laporte, Federico PasinAbstract:This paper introduces an iterated Tabu Search heuristic for the daily car sequencing problem in which a set of cars must be sequenced so as to satisfy requirements from the paint shop and the assembly line. The iterated Tabu Search heuristic combines a classical Tabu Search with perturbation operators that help escape from local optima. The resulting heuristic is flexible, easy to implement, and fast. It has produced very good results on a set of test instances provided by the French car manufacturer Renault.
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Tabu Search Heuristics for the Vehicle Routing Problem
Operations Research Computer Science Interfaces Series, 1Co-Authors: Jean-françois Cordeau, Gilbert LaporteAbstract:This article reviews some of the most important Tabu Search heuristics for the vehicle routing problem. Some of the main Tabu Search features are first described: neighbourhood structures, short term memory, long term memory, intensification. The Tabu Search algorithms are then described, followed by computational results and the conclusion.
