Proceedings ArticleDOI
Adaptive genetic algorithm using harmony search
Farhad Nadi,Ahamad Tajudin Khader,Mohammed Azmi Al-Betar +2 more
- pp 819-820
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TLDR
This paper proposes an adaptive parameter controlling approach using harmony search that directs the search from the current state to a desired state by determining suitable parameter values such that the balance between exploration and exploitation is suitable for that state transition.Abstract:
Evolutionary algorithm is one of the major classes of stochastic search methods. This algorithm searches the problem space by exploring and exploiting the search space. The balance between exploration and exploitation will change throughout the search process. Maintaining the right balance between the exploration and exploitation in the search process is crucial for the success of the search process. The parameter values of the algorithm play a crucial role in determining the nature of the search, whether explorative or exploitative. In this paper, we propose an adaptive parameter controlling approach using harmony search. During the search process, harmony search directs the search from the current state to a desired state by determining suitable parameter values such that the balance between exploration and exploitation is suitable for that state transition. The preliminary results of the proposed method is comparable with those from the literature.read more
Citations
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Journal ArticleDOI
The variants of the harmony search algorithm: an overview
TL;DR: An overview of improvements in terms of parameters setting and hybridizing HS components with other metaheuristic algorithms is presented, with a goal of providing useful references to fundamental concepts accessible to the broad community of optimization practitioners.
Journal ArticleDOI
Comprehensive Review of the Development of the Harmony Search Algorithm and its Applications
TL;DR: This paper presents a comprehensive overview of the development of the harmony search (HS) algorithm and its applications, and describes the HS algorithm and present how its parameters affect algorithm performance.
Journal ArticleDOI
A hybrid harmony search algorithm for ab initio protein tertiary structure prediction
Mohammed Said Abual-Rub,Mohammed Azmi Al-Betar,Mohammed Azmi Al-Betar,Rosni Abdullah,Ahamad Tajudin Khader +4 more
TL;DR: This study introduces a hybrid harmony search algorithm (HHSA) as a means to solve ab initio protein tertiary structure prediction problem and shows that the algorithm can find more precise solutions than other previous studies.
Journal ArticleDOI
Solving the conditional and unconditional p-center problem with modified harmony search: A real case study
Ali Kaveh,H. Nasr +1 more
TL;DR: This paper solves the well-known conditional and unconditional p -center problem using a modified harmony search algorithm and presents some results for other meta-heuristic algorithms including the variable neighborhood search, the Tabu search, and the scatter search.
Journal ArticleDOI
Hybrid Harmony Search Algorithms
Nazmul Siddique,Hojjat Adeli +1 more
TL;DR: This article presents a review of hybrid harmony search algorithms, a music-inspired population-based meta-heuristic search and optimization algorithm that combines HSA with other algorithms to improve exploration or global search ability and increase convergence speed.
References
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Journal Article
Evolutionary algorithms with on-the-fly population size adjustment
TL;DR: The experiments show that the population (re)sizing mechanisms exhibit significant differences in speed, measured by the number of fitness evaluations to a solution and the best EAs with adaptive population resizing outperform the traditional genetic algorithm (GA) by a large margin.
Book ChapterDOI
Evolutionary Algorithms with On-the-Fly Population Size Adjustment
TL;DR: In this article, the authors evaluate on-the-fly population re-sizing mechanisms for evolutionary algorithms (EAs) in terms of success rate, speed and solution quality, measured on a variety of fitness landscapes.
Book ChapterDOI
New Ways to Calibrate Evolutionary Algorithms
Gusz Eiben,Martijn C. Schut +1 more
TL;DR: The case study on adjusting tournament size shows by example that global parameters can also be selfadapted, and that heuristic adaptation and pure self-adaptation can be successfully combined into a hybrid of the two.
Proceedings ArticleDOI
Parameter calibration using meta-algorithms
TL;DR: Comparative experiments on a set of randomly generated problem instances with various levels of multi-modality show that GAs calibrated with REVAC can outperform those calibrated by hand and by the meta-GA.
Book ChapterDOI
Is self-adaptation of selection pressure and population size possible?: a case study
TL;DR: This paper designs and executes experiments for comparing the performance increase of a benchmark EA when augmented with self-adaptive control of parameters concerning selection and population size in isolation and in combination and observes that self- Adapting selection yields the highest benefit in terms of speed.