Analysis of speciation and niching in the multi-niche crowding GA
Theoretical Computer Science - Special issue on evolutionary computation
Memetic algorithms: a short introduction
New ideas in optimization
Cliques, Coloring, and Satisfiability: Second DIMACS Implementation Challenge, Workshop, October 11-13, 1993
Uniform Crossover in Genetic Algorithms
Proceedings of the 3rd International Conference on Genetic Algorithms
Diversity-Guided Evolutionary Algorithms
PPSN VII Proceedings of the 7th International Conference on Parallel Problem Solving from Nature
An analysis of the behavior of a class of genetic adaptive systems.
An analysis of the behavior of a class of genetic adaptive systems.
Searching for diverse, cooperative populations with genetic algorithms
Evolutionary Computation
A Metaheuristic Approach for the Vertex Coloring Problem
INFORMS Journal on Computing
A search space "cartography" for guiding graph coloring heuristics
Computers and Operations Research
MA|PM: memetic algorithms with population management
Computers and Operations Research
Computers and Operations Research
A fast and elitist multiobjective genetic algorithm: NSGA-II
IEEE Transactions on Evolutionary Computation
Diversity in genetic programming: an analysis of measures and correlation with fitness
IEEE Transactions on Evolutionary Computation
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We introduce the Spacing Memetic Algorithm (SMA), a formal evolutionary model devoted to a systematic control of spacing (distances) among individuals. SMA uses search space distance information to decide what individuals are acceptable in the population, what individuals need to be replaced and when to apply mutations. By ensuring a "healthy" spacing (and thus diversity), SMA substantially reduces the risk of premature convergence and helps the search process to continuously discover new high-quality search areas. Generally speaking, the number of distance calculations represents a limited computational overhead compared to the number of local search iterations. Most existing memetic algorithms can be "upgraded" to a spacing memetic algorithm, provided that a suitable distance measure can be specified. The impact of the main SMA components is assessed within several case studies on different problems.