Genetic algorithms with sharing for multimodal function optimization
Proceedings of the Second International Conference on Genetic Algorithms on Genetic algorithms and their application
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
An Investigation of Niche and Species Formation in Genetic Function Optimization
Proceedings of the 3rd International Conference on Genetic Algorithms
Resource-Based Fitness Sharing
PPSN VII Proceedings of the 7th International Conference on Parallel Problem Solving from Nature
Optimal Nesting of Species for Exact Cover: Many against Many
Proceedings of the 10th international conference on Parallel Problem Solving from Nature: PPSN X
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Recent success with a simple type of coevolution, resource defined fitness sharing (RFS), involving only pairwise interactions among species, has inspired some static analysis of the species interaction matrix. Under the assumption of equilibrium (w.r.t. selection), the matrix yields a set of linear equations. If there exists a subset of species that exactly cover the resources, then its characteristic population vector is a solution to the equilibrium equations. And if the matrix is non-singular, a solution to the equilibrium equations specifies an exact cover of the resources. This polynomial-time reduction of exact cover problems to linear equations is used in this paper to transform certain exact cover NP-complete problems to certain linear equation NP-complete problems: 0-1 Integer Programming, Minimum Weight Positive Solution to Linear Equations. While most of these problems are known to be in NP-complete, our new proof technique introduces a practical, polynomial-time heuristic algorithm for solving large instances of them.