Partial constraint satisfaction
Artificial Intelligence - Special volume on constraint-based reasoning
Swarm intelligence: from natural to artificial systems
Swarm intelligence: from natural to artificial systems
MadKit: a generic multi-agent platform
AGENTS '00 Proceedings of the fourth international conference on Autonomous agents
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Computing lower bound for MAX-CSP problems
IEA/AIE'2003 Proceedings of the 16th international conference on Developments in applied artificial intelligence
The Approximability of Three-valued MAX CSP
SIAM Journal on Computing
Parallel Combinatorial Optimization (Wiley Series on Parallel and Distributed Computing)
Parallel Combinatorial Optimization (Wiley Series on Parallel and Distributed Computing)
Load Balancing for the Dynamic Distributed Double Guided Genetic Algorithm for MAX-CSPs
International Journal of Artificial Life Research
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In this article, we propose new approaches for maximal constraint satisfaction problems (Max-CSPs), inspired by the marriage process of honeybees. Our approaches consist on honeybees for optimization and constraint reasoning. The first one is centralized and the second one is distributed. Our approaches are enhanced by a new parameter. Experimental comparison between the two approaches and their explanations are provided. Compared to the Dynamic Distributed Double Guided Genetic Algorithm, the Distributed Honeybee Algorithm for Optimization and Constraint Reasoning is better in term of solution quality.