New Heuristics and Lower Bounds for the Min-Max k -Chinese Postman Problem
ESA '02 Proceedings of the 10th Annual European Symposium on Algorithms
Social coordination without communication in multi-agent territory exploration tasks
AAMAS '06 Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems
Web Intelligence and Agent Systems
Investigating the Adaptiveness of Communication in Multi-Agent Behavior Coordination
Adaptive Behavior - Animals, Animats, Software Agents, Robots, Adaptive Systems
Multilocus consensus genetic maps (MCGM): Formulation, algorithms, and results
Computational Biology and Chemistry
Power-switch routing for coarse-grain MTCMOS technologies
Proceedings of the 2009 International Conference on Computer-Aided Design
The effect of the asymmetry of road transportation networks on the traveling salesman problem
Computers and Operations Research
LION'12 Proceedings of the 6th international conference on Learning and Intelligent Optimization
Proceedings of the twelfth workshop on Foundations of genetic algorithms XII
Proceedings of the 15th annual conference companion on Genetic and evolutionary computation
Annals of Mathematics and Artificial Intelligence
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We use a branch-and-cut search to solve the Whizzkids'96 vehicle routing problem, demonstrating that the winning solution in the 1996 competition is in fact optimal. Our algorithmic framework combines the LP-based traveling salesman code of Applegate, Bixby, Chv脙隆tal, and Cook, with specialized cutting planes and a distributed search algorithm, permitting the use of a computing network located across Rice, Princeton, AT&T, and Bonn. The 1996 problem instance wasdeveloped by E. Aartsand J. K. Lenstra, and the competition was sponsored by the information technology firm CMG and the newspaper De Telegraaf.