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An Improved Tabu Search Algorithm for Continuous Global Optimization Problems

Yue Xiao-hui

Open publisher page 1 citations

Abstract

Tabu search algorithm is a meta-heuristic global optimization algorithm,which has been successfully applied to a variety of combination optimization problems.This paper proposes an improved memory-based tabu search algorithm,which is applied as an approach to solve continuous function optimization on closed bounded region.The proposed algorithm is very simple and easy to implement.Numerical results illustrate that this algorithm is feasible,effective,and very suitable for continuous global optimization.

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What this paper is about

Tabu search algorithm is a meta-heuristic global optimization algorithm,which has been successfully applied to a variety of combination optimization problems.This paper proposes an improved memory-based tabu search algorithm,which is applied as an approach to solve continuous function optimization on closed bounded region.The proposed algorithm is very simple and easy to implement.Numerical results illustrate that this algorithm is feasible,effective,and very suitable for continuous global optimization.

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OpenAlex reports 1 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

Tabu search algorithm is a meta-heuristic global optimization algorithm,which has been successfully applied to a variety of combination optimization problems.This paper proposes an improved memory-based tabu search algorithm,which is applied as an approach to solve continuous function optimization on closed bounded region.The proposed algorithm is very simple and easy to implement.Numerical results illustrate that this algorithm is feasible,effective,and very suitable for continuous global optimization.

Key concepts: Tabu search, Mathematical optimization, Guided Local Search, Algorithm, Global optimization, Computer science, Continuous optimization, Metaheuristic

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