A comprehensive survey: artificial bee colony (ABC) algorithm and applications

Artificial Intelligence Review, Journal Year: 2012, Volume and Issue: 42(1), P. 21 - 57

Published: March 10, 2012

Language: Английский

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Constraint-handling in nature-inspired numerical optimization: Past, present and future

Swarm and Evolutionary Computation, Journal Year: 2011, Volume and Issue: 1(4), P. 173 - 194

Published: Nov. 5, 2011

Language: Английский

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Classification of adaptive memetic algorithms: a comparative study

IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics), Journal Year: 2006, Volume and Issue: 36(1), P. 141 - 152

Published: Jan. 25, 2006

Adaptation of parameters and operators represents one the recent most important promising areas research in evolutionary computations; it is a form designing self-configuring algorithms that acclimatize to suit problem hand. Here, our interests are on breed hybrid typically known as adaptive memetic (MAs). One unique feature MAs choice local search methods or memes studies have shown this significantly affects performances searches. In paper, we present classification adaptation basis mechanism used level historical knowledge employed. Then asymptotic convergence properties considered analyzed according classification. Subsequently, empirical representatives for different type-level meme adaptations using continuous benchmark problems indicate global-level exhibit better performances. Finally conclude with some directions area.

Language: Английский

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A survey of search methodologies and automated system development for examination timetabling

Journal of Scheduling, Journal Year: 2008, Volume and Issue: 12(1), P. 55 - 89

Published: Oct. 28, 2008

Language: Английский

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A Survey of Automatic Parameter Tuning Methods for Metaheuristics

IEEE Transactions on Evolutionary Computation, Journal Year: 2019, Volume and Issue: 24(2), P. 201 - 216

Published: June 7, 2019

Parameter tuning, that is, to find appropriate parameter settings (or configurations) of algorithms so their performance is optimized, an important task in the development and application metaheuristics. Automating this task, i.e., developing algorithmic procedure address tuning highly desired has attracted significant attention from researchers practitioners. During last two decades, many automatic approaches have been proposed. This paper presents a comprehensive survey methods for A new classification taxonomy) introduced according structure methods. The existing are consequently classified into three categories: 1) simple generate-evaluate methods; 2) iterative 3) high-level Then, these categories reviewed sequence. In addition description each method, its main strengths weaknesses discussed, which helpful or practitioners select use. Furthermore, some challenges directions field pointed out further research.

Language: Английский

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Operational Optimization of Water Distribution Systems Using a Hybrid Genetic Algorithm

Journal of Water Resources Planning and Management, Journal Year: 2004, Volume and Issue: 130(2), P. 160 - 170

Published: Feb. 20, 2004

Genetic algorithm (GA) optimization is well suited for optimizing the operation of water distribution systems, especially large and complex systems. GAs have good initial convergence characteristics, but slow down considerably once region optimal solution has been identified. In this study efficiency GA operational was improved through a hybrid method which combines with hillclimber search strategy. Hillclimber strategies complement by being efficient in finding local optimum. Two strategies, Hooke Jeeves Fibonacci methods, were investigated. The proved to be superior pure quickly, both when applied test problem existing system.

Language: Английский

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TREATING CONSTRAINTS AS OBJECTIVES FOR SINGLE-OBJECTIVE EVOLUTIONARY OPTIMIZATION

Engineering Optimization, Journal Year: 2000, Volume and Issue: 32(3), P. 275 - 308

Published: Jan. 1, 2000

Abstract This paper presents a new approach to handle constraints using evolutionary algorithms. The technique treats as objectives, and uses multiobjective optimization solve the re-stated single-objective problem. is compared against other numerical techniques in several engineering problems with different kinds of constraints. results obtained show that can consistently outperform relatively small sub-populations, without significant sacrifice terms performance.

Language: Английский

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Methods for the Analysis of Evolutionary Algorithms on Pseudo-Boolean Functions

Kluwer Academic Publishers eBooks, Journal Year: 2006, Volume and Issue: unknown, P. 349 - 369

Published: Feb. 24, 2006

Language: Английский

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Analog circuit optimization system based on hybrid evolutionary algorithms

Integration, Journal Year: 2008, Volume and Issue: 42(2), P. 137 - 148

Published: April 21, 2008

Language: Английский

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Circle detection using electro-magnetism optimization

Information Sciences, Journal Year: 2011, Volume and Issue: 182(1), P. 40 - 55

Published: Jan. 10, 2011

Language: Английский

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