Publication

Tabu search techniques - A tutorial and an application to neural networks

Dominique de Werra, Alain Hertz
1989

Abstract

Tabu Search is a general heuristic procedure for global optimization. Based on simple ideas it has been extremely efficient in getting almost optimal solutions for many types of difficult combinatorial optimization problems. The principles of Tabu Search are discribed and illustrations are given. An example of problem type where the use of Tabu Search has drastically cut down the computational effort is presented; it consists of the learning process of an associative memory represented by a neural network.

Official source

https://infoscience.epfl.ch/entities/publication/2deaf7f0-f056-4719-abb0-389df1672022

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Dominique de Werra, Alain Hertz
1989

Abstract

Official source

https://infoscience.epfl.ch/entities/publication/2deaf7f0-f056-4719-abb0-389df1672022

About this result

Related concepts (32)

Metaheuristic

In computer science and mathematical optimization, a metaheuristic is a higher-level procedure or heuristic designed to find, generate, tune, or select a heuristic (partial search algorithm) that may provide a sufficiently good solution to an optimization problem or a machine learning problem, especially with incomplete or imperfect information or limited computation capacity. Metaheuristics sample a subset of solutions which is otherwise too large to be completely enumerated or otherwise explored.

Global optimization

Global optimization is a branch of applied mathematics and numerical analysis that attempts to find the global minima or maxima of a function or a set of functions on a given set. It is usually described as a minimization problem because the maximization of the real-valued function is equivalent to the minimization of the function . Given a possibly nonlinear and non-convex continuous function with the global minima and the set of all global minimizers in , the standard minimization problem can be given as that is, finding and a global minimizer in ; where is a (not necessarily convex) compact set defined by inequalities .

Mathematical optimization

Mathematical optimization (alternatively spelled optimisation) or mathematical programming is the selection of a best element, with regard to some criterion, from some set of available alternatives. It is generally divided into two subfields: discrete optimization and continuous optimization. Optimization problems arise in all quantitative disciplines from computer science and engineering to operations research and economics, and the development of solution methods has been of interest in mathematics for centuries.

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Tabu search techniques - A tutorial and an application to neural networks

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