Evolutionary search guided by the constraint network to solve CSP

We are interested in defining a general evolutionary algorithm to solve constraint satisfaction problems, which takes into account both advantages of the systematic and traditional methods and of characteristics of the CSP. In this context knowledge about properties of the constraint network has allowed us to define a fitness function, for evaluation (Riff, 1996). We introduce two new operators which look at the constraint network during evolution. The first one is a bisexual operator like crossover denominated arc-crossover, for exploitation. The second one is an operator like mutation called arc-mutation, for exploration. These operators are used to improve the stochastic search.

[1]  Rina Dechter,et al.  Enhancement Schemes for Constraint Processing: Backjumping, Learning, and Cutset Decomposition , 1990, Artif. Intell..

[2]  A. E. Eiben,et al.  Self-adaptivity for constraint satisfaction: learning penalty functions , 1996, Proceedings of IEEE International Conference on Evolutionary Computation.

[3]  Eugene C. Freuder.  A Sufficient Condition for Backtrack-Free Search , 1982, JACM.

[4]  Hachemi Bennaceur,et al.  A Labelling Arc Consistency Method for Functional Constraints , 1996, CP.

[5]  James Bowen,et al.  Solving small and large scale constraint satisfaction problems using a heuristic-based microgenetic algorithm , 1994, Proceedings of the First IEEE Conference on Evolutionary Computation. IEEE World Congress on Computational Intelligence.

[6]  James Bowen,et al.  Solving Constraint Satisfaction Problems Using a Genetic/Systematic Search Hybrid That Realizes When to Quit , 1995, ICGA.

[7]  M. Rojas,et al.  Using the knowledge of the constraints network to design an evolutionary algorithm that solves CSP , 1996 .

[8]  A. E. Eiben,et al.  Solving constraint satisfaction problems using genetic algorithms , 1994, Proceedings of the First IEEE Conference on Evolutionary Computation. IEEE World Congress on Computational Intelligence.

[9]  Steven Minton,et al.  Minimizing Conflicts: A Heuristic Repair Method for Constraint Satisfaction and Scheduling Problems , 1992, Artif. Intell..

[10]  Robert M. Haralick,et al.  Increasing Tree Search Efficiency for Constraint Satisfaction Problems , 1979, Artif. Intell..

[11]  Vipin Kumar,et al.  Algorithms for Constraint-Satisfaction Problems: A Survey , 1992, AI Mag..

[12]  Edward P. K. Tsang,et al.  Applying Genetic Algorithms to Constraint Satisfaction Optimization Problems , 1990, ECAI.