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An opposition-based algorithm for function optimization

ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE 2015年 37卷 293-306页

作者： Seif, Z. Ahmadi, M. B. Shiraz Univ Coll Sci Dept Math Shiraz 71454 Iran

The concept of opposition-based learning (OBL) was first introduced as a scheme for machine intelligence. In a very short period of time, some other variants of opposite numbers were proposed and opposition was applied to various research areas. In metaheuristic optimization algorithms, the main idea behind applying opposite numbers is the simultaneous consideration of a candidate solution and its corresponding opposite candidate in order to achieve a better approximation for the current solution. This paper proposes an opposition-based metaheuristic optimization algorithm (OBA) and a new and efficient opposition named comprehensive opposition (CO) as its main operator. In this paper it is mathematically proven that CO not only increases the chance of achieving better approximations for the solution but also guarantees the global convergence of OBA. The efficiency of the proposed method has been compared with some well-known heuristic search methods. The obtained results confirm the high performance of the proposed method in solving various function optimizations. (C) 2014 Elsevier Ltd. All rights reserved.

关键词： Metaheuristic opposition-based algorithm Comprehensive opposition Parametric programming Global convergence Markov chain

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A Convergence algorithm for Function Optimization

A Convergence Algorithm for Function Optimization

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Future Technologies Conference (FTC)

作者： Ahmadi, M. B. Seif, Z. Shiraz Univ Dept Math Shiraz Iran

ISBN: (纸本)9781509041718

This paper proposes an opposition-based metaheuristic optimization algorithm. The global convergence of the algorithm is guaranteed. The efficiency of the proposed method has been compared with some well-known heuristic search methods. The obtained results confirm the high performance of the proposed method in solving various function optimizations.

关键词： metaheuristic opposition-based algorithm comprehensive opposition parametric programming global convergence

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