Swarm intelligence: from natural to artificial systems
Swarm intelligence: from natural to artificial systems
MACS-VRPTW: a multiple ant colony system for vehicle routing problems with time windows
New ideas in optimization
Modeling transportation problems using concepts of swarm intelligence and soft computing
Modeling transportation problems using concepts of swarm intelligence and soft computing
Ant Colony Optimization
On Honey Bees and Dynamic Server Allocation in Internet Hosting Centers
Adaptive Behavior - Animals, Animats, Software Agents, Robots, Adaptive Systems
A bee colony optimization algorithm to job shop scheduling
Proceedings of the 38th conference on Winter simulation
Exchange strategies for multiple Ant Colony System
Information Sciences: an International Journal
A general heuristic for vehicle routing problems
Computers and Operations Research
A Two-Stage Hybrid Local Search for the Vehicle Routing Problem with Time Windows
Transportation Science
Vehicle Routing Problem with Time Windows, Part II: Metaheuristics
Transportation Science
Journal of Global Optimization
Ant colony system: a cooperative learning approach to the traveling salesman problem
IEEE Transactions on Evolutionary Computation
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The paper presents a new optimization algorithm, which adapts the behavior of honey bees during their search for nectar. In addition to the established ant algorithms, bee-inspired algorithms represent a relatively young form of solution procedures, whose applicability to the solution of complex optimization problems has already been shown. The herein presented two-stage approach belongs to the class of metaheuristics to control a construction heuristic and has been applied successfully to the NP-hard Vehicle Routing Problem with Time Windows (VRPTW). Within the paper, evaluation results are presented, which compare the developed algorithm to some of the most successful procedures for the solution of benchmark problems. The pursued approach gives the best results so far for a metaheuristic to control a construction heuristic.