Journal ArticleDOI
Memetic Algorithms: The Polynomial Local Search Complexity Theory Perspective
Natalio Krasnogor,James C. Smith +1 more
Reads0
Chats0
TLDR
It is pointed out in this paper that memetic algorithms for graph partitioning and maximum network flow (both with important practical applications) also give rise to PLS-complete problems.Abstract:
In previous work (Krasnogor, http://www.cs.nott.ac.uk/~nxk/papers.html. In: Studies on the Theory and Design Space of Memetic Algorithms. Ph.D. thesis, University of the West of England, Bristol, UK, 2002; Krasnogor and Smith, IEEE Trans Evol Algorithms 9(6):474–488, 2005) we develop a syntax-only classification of evolutionary algorithms, in particular so-called memetic algorithms (MAs). When “syntactic sugar” is added to our model, we are able to investigate the polynomial local search (PLS) complexity of memetic algorithms. In this paper we show the PLS-completeness of whole classes of problems that occur when memetic algorithms are applied to the travelling salesman problem using a range of mutation, crossover and local search operators. Our PLS-completeness results shed light on the worst case behaviour that can be expected of a memetic algorithm under these circumstances. Moreover, we point out in this paper that memetic algorithms for graph partitioning and maximum network flow (both with important practical applications) also give rise to PLS-complete problems.read more
Citations
More filters
Journal ArticleDOI
Memetic algorithms and memetic computing optimization: A literature review
Ferrante Neri,Carlos Cotta +1 more
TL;DR: Several classes of optimization problems, such as discrete, continuous, constrained, multi-objective and characterized by uncertainties, are addressed by indicating the memetic “recipes” proposed in the literature.
Journal ArticleDOI
A Multi-Facet Survey on Memetic Computation
TL;DR: A comprehensive multi-facet survey of recent research in memetic computation is presented and includes simple hybrids, adaptive hybrids and memetic automaton.
Book ChapterDOI
A Modern Introduction to Memetic Algorithms
Pablo Moscato,Carlos Cotta +1 more
TL;DR: This work shows the general structure of memetic algorithms, including some guidelines for their design, and offers an overview of the numerous applications of these techniques and a sketch of the current development trends.
Journal ArticleDOI
The impact of parametrization in memetic evolutionary algorithms
TL;DR: This work considers a simple memetic algorithm for pseudo-Boolean optimization that captures basic working principles of memetic algorithms-the interplay of genetic operators like mutation and selection with local search and shows exemplarily that parametrizing memetic evolutionary algorithms can be extremely hard.
Journal ArticleDOI
Adaptive cellular memetic algorithms
TL;DR: This paper extends the notion of cellularity to memetic algorithms (MA), a configuration termed cellular memetic algorithm (CMA), and proposes adaptive mechanisms that tailor the amount of exploration versus exploitation of local solutions carried out by the CMA.
References
More filters
Journal ArticleDOI
No free lunch theorems for optimization
TL;DR: A framework is developed to explore the connection between effective optimization algorithms and the problems they are solving and a number of "no free lunch" (NFL) theorems are presented which establish that for any algorithm, any elevated performance over one class of problems is offset by performance over another class.
Book
Handbook of Evolutionary Computation
TL;DR: The Oxford University Press and the Institute of Physics have joined forces to create a major reference publication devoted to EC fundamentals, models, algorithms and applications, intended to become the standard reference resource for the evolutionary computation community.
Book
Local Search in Combinatorial Optimization
TL;DR: Local search is still the method of choice for NP-hard problems as it provides a robust approach for obtaining high-quality solutions to problems of a realistic size in a reasonable time.
Journal ArticleDOI
Variable neighborhood search: Principles and applications
Pierre Hansen,Nenad Mladenović +1 more
TL;DR: In this article, a simple and effective metaheuristic for combinatorial and global optimization, called variable neighborhood search (VNS), is presented, which can easily be implemented using any local search algorithm as a subroutine.
On Evolution, Search, Optimization, Genetic Algorithms and Martial Arts : Towards Memetic Algorithms
TL;DR: In this paper, the authors present a short abstract, which is a summary of the paper.Short abstract, isn't it? But it is short abstracts, not abstracts.
Related Papers (5)
A tutorial for competent memetic algorithms: model, taxonomy, and design issues
Natalio Krasnogor,James C. Smith +1 more