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Fundamentals of scatter search and path relinking
 CONTROL AND CYBERNETICS
, 2000
"... The evolutionary approach called Scatter Search, and its generalized form called Path Relinking, have proved unusually effective for solving a diverse array of optimization problems from both classical and real world settings. Scatter Search and Path Relinking differ from other evolutionary procedur ..."
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Cited by 139 (13 self)
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The evolutionary approach called Scatter Search, and its generalized form called Path Relinking, have proved unusually effective for solving a diverse array of optimization problems from both classical and real world settings. Scatter Search and Path Relinking differ from other evolutionary procedures, such as genetic algorithms, by providing unifying principles for joining solutions based on generalized path constructions (in both Euclidean and neighborhood spaces) and by utilizing strategic designs where other approaches resort to randomization. Scatter Search and Path Relinking are also intimately related to the Tabu Search metaheuristic, and derive additional advantages by making use of adaptive memory and associated memoryexploiting mechanisms that are capable of being adapted to particular contexts. We describe the features of Scatter Search and Path Relinking that set them apart from other evolutionary approaches, and that offer opportunities for creating increasingly more versatile and effective methods in the future.
A Tutorial for Competent Memetic Algorithms: Model, Taxonomy, and Design Issues
 IEEE Transactions on Evolutionary Computation
, 2005
"... We recommend you cite the published version. ..."
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A gentle introduction to memetic algorithms
 Handbook of Metaheuristics
, 2003
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Fitness Landscapes and Memetic Algorithm Design
 New Ideas in Optimization
, 1999
"... Introduction The notion of fitness landscapes has been introduced to describe the dynamics of evolutionary adaptation in nature [40] and has become a powerful concept in evolutionary theory. Fitness landscapes are equally well suited to describe the behavior of heuristic search methods in optimizat ..."
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Cited by 70 (8 self)
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Introduction The notion of fitness landscapes has been introduced to describe the dynamics of evolutionary adaptation in nature [40] and has become a powerful concept in evolutionary theory. Fitness landscapes are equally well suited to describe the behavior of heuristic search methods in optimization, since the process of evolution can be thought of as searching a collection of genotypes in order to find the genotype of an organism with highest fitness and thus highest chance of survival. Thinking of a heuristic search method as a strategy to "navigate" in the fitness landscape of a given optimization problem may help in predicting the performance of a heuristic search algorithm if the structure of the landscape is known in advance. Furthermore, the analysis of fitness landscapes may help in designing highly effective search algorithms. In the following we show how the analysis of fitness landscapes of combinatorial optimization problems can aid in designing the components of
Fitness Variance of Formae and Performance Prediction
, 1994
"... Representation is widely recognised as a key determinant of performance in evolutionary computation. The development of families of representationindependentoperators allows the formulation of formal representationindependent evolutionary algorithms. These formal algorithms can be instantiated ..."
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Cited by 66 (7 self)
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Representation is widely recognised as a key determinant of performance in evolutionary computation. The development of families of representationindependentoperators allows the formulation of formal representationindependent evolutionary algorithms. These formal algorithms can be instantiated for particular search problems by selecting a suitable representation. The performance of different representations, in the context of any given formal representationindependent algorithm, can then be measured. Simple analyses suggest that fitness variance of formae (generalised schemata) for the chosen representation might act as a performance predictor for evolutionary algorithms. This hypothesis is tested and supported through studies of four different representations for the travelling salesrep problem (TSP) in the context of both formal representationindependentgenetic algorithms and corresponding memetic algorithms. 1 Motivation The subject of this paper is representation i...
Fundamental Limitations on Search Algorithms: Evolutionary Computing in Perspective
 LECTURE NOTES IN COMPUTER SCIENCE 1000
, 1995
"... The past twenty years has seen a rapid growth of interest in stochastic search algorithms, particularly those inspired by natural processes in physics and biology. Impressive results have been demonstrated on complex practical optimisation problems and related search applications taken from a var ..."
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Cited by 60 (1 self)
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The past twenty years has seen a rapid growth of interest in stochastic search algorithms, particularly those inspired by natural processes in physics and biology. Impressive results have been demonstrated on complex practical optimisation problems and related search applications taken from a variety of fields, but the theoretical understanding of these algorithms remains weak. This results partly from the insufficient attention that has been paid to results showing certain fundamental limitations on universal search algorithms, including the socalled "No Free Lunch" Theorem. This paper extends these results and draws out some of their implications for the design of search algorithms, and for the construction of useful representations. The resulting insights focus attention on tailoring algorithms and representations to particular problem classes by exploiting domain knowledge. This highlights the fundamental importance of gaining a better theoretical grasp of the ways i...
Memetic Algorithms for Combinatorial Optimization Problems: Fitness Landscapes and Effective Search Strategies
, 2001
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Memetic Algorithms for the Traveling Salesman Problem
 Complex Systems
, 1997
"... this paper, the tness landscapes of several instances of the traveling salesman problem (TSP) are investigated to illustrate why MAs are wellsuited for nding nearoptimum tours for the TSP. It is shown that recombination{based MAs can exploit the correlation structure of the landscape. A comparis ..."
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Cited by 37 (8 self)
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this paper, the tness landscapes of several instances of the traveling salesman problem (TSP) are investigated to illustrate why MAs are wellsuited for nding nearoptimum tours for the TSP. It is shown that recombination{based MAs can exploit the correlation structure of the landscape. A comparison of several recombination operators { including a new generic recombination operator { reveals that when using the sophisticated Lin{Kernighan local search, the performance dierence of the MAs is small. However, the most important property of eective recombination operators is shown to be respectfulness. In experiments it is shown that our MAs with generic recombination are among the best evolutionary algorithms for the TSP. In particular, optimum solutions could be found up to a problem size of 3795, and for large instances up to 85,900 cities, nearoptimum solutions could be found in a reasonable amount of time
Application of a Hybrid MultiObjective Evolutionary Algorithm to the Uncapacitated Exam Proximity Problem
 eds): Proceedings of the 5th International Conference on Practice and Theory of Automated Timetabling (PATAT 2004
, 2004
"... A hybrid MultiObjective Evolutionary Algorithm is used to tackle the uncapacitated exam proximity problem. In this hybridization, local search operators are used instead of the traditional genetic recombination operators. One of the search operators is designed to repair unfeasible timetables p ..."
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Cited by 25 (0 self)
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A hybrid MultiObjective Evolutionary Algorithm is used to tackle the uncapacitated exam proximity problem. In this hybridization, local search operators are used instead of the traditional genetic recombination operators. One of the search operators is designed to repair unfeasible timetables produced by the initialization procedure and the mutation operator. The other search operator implements a simplified Variable Neighborhood Descent metaheuristic and its role is to improve the proximity cost. The resulting non dominated timetables are compared with thouse produced by other optimization methods using 15 public domain datasets. Without special finetuning, the hybrid algorithm was able to produce timetables ranking first and second in 9 of the 15 datasets.
Myths and Legends of the Baldwin Effect
, 1996
"... This position paper argues that the Baldwin effect is widely misunderstood by the evolutionary computation community. The misunderstandings appear to fall into two general categories. Firstly, it is commonly believed that the Baldwin effect is concerned with the synergy that results when there is an ..."
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Cited by 24 (0 self)
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This position paper argues that the Baldwin effect is widely misunderstood by the evolutionary computation community. The misunderstandings appear to fall into two general categories. Firstly, it is commonly believed that the Baldwin effect is concerned with the synergy that results when there is an evolving population of learning individuals. This is only half