نتایج جستجو برای: intensification and diversification phases

تعداد نتایج: 16838735  

2017
Jean-Yves Potvin

This chapter presents the fundamental concepts of tabu search (TS) in a tutorial fashion. Special emphasis is put on showing the relationships with classical local search methods and on the basic elements of any TS heuristic, namely the definition of the search space, the neighborhood structure, and the search memory. Other sections cover other important concepts such as search intensification ...

2005
Víctor Robles José M. Peña María S. Pérez-Hernández Pilar Herrero Óscar Cubo

Hybrid metaheuristics have received considerable interest in recent years. Since several years ago, a wide variety of hybrid approaches have been proposed in the literature including the new GA-EDA approach. We have design and implemented an extension to this GA-EDA approach, based on statistical significance tests. This approach had allowed us to make an study of the balance of diversification...

2005
Mercedes C. Carnero José L. Hernández Mabel C. Sánchez

In this work a Tabu Search heuristic is proposed to solve the optimal design and upgrade of sensor structures that satisfy both economic criteria and specific requirements on key variable estimates. The heuristic is based on the Strategic Oscillation Technique around the feasibility boundary, a procedure that has good intensification and diversification capabilities. Comparative performance stu...

2006
Yi HE Guangyuan LIU Yuhui QIU

We presented a parallel tabu search (PTS) algorithm for the traveling salesman problem (TSP), which is NP-hard. To parallelize tabu search (TS) algorithm efficiently, the search space decomposition based on partition principle was used to balance the computing load, while exploitation in subspace had been boosted by an adaptive search strategy of intensification and diversification. Numerical r...

2014
Pauline Ong

Modification of the intensification and diversification approaches in the recently developed cuckoo search algorithm (CSA) is performed. The alteration involves the implementation of adaptive step size adjustment strategy, and thus enabling faster convergence to the global optimal solutions. The feasibility of the proposed algorithm is validated against benchmark optimization functions, where t...

Journal: :J. Heuristics 2006
Sin C. Ho Michel Gendreau

This paper describes a tabu search heuristic with path relinking for the vehicle routing problem. Tabu search is a local search method that explores the solution space more thoroughly than other local search based methods by overcoming local optima. Path relinking is a method to integrate intensification and diversification in the search. It explores paths that connect previously found elite so...

2005
Michel Gendreau

This paper presents the fundamental concepts of Tabu Search (TS) in a tutorial fashion. Special emphasis is put on showing the relationships with classical Local Search methods and on the basic elements of any TS heuristic, namely, the definition of the search space, the neighborhood structure, and the search memory. Other sections cover other important concepts such as search intensification a...

Journal: :JDCTA 2010
Yongguo Liu Jianrui Hao

In this article, a novel approach is proposed to predict RNA secondary structure called RNA secondary structure prediction based on Tabu Search (RNATS). In the RNATS algorithm, two search models, intensification search and diversification search, are developed to exploit the local regions around the current solution and explore the unvisited solution space, respectively. Simulation experiments ...

2009
S. L. Ho Shiyou Yang Guangzheng Ni H. C. Wong

An extended Tabu algorithm with an aspiration factor is proposed. The algorithm is based on the success of techniques such as the memorization of the previously visited subspaces, the systematic diversification as well as the intensification process for neighborhood creations. The numerical results obtained by solving a mathematical test function and the benchmark problem 22 of the TEAM Worksho...

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