The vehicle routing problem
Expanding Neighborhood GRASP for the Traveling Salesman Problem
Computational Optimization and Applications
A general heuristic for vehicle routing problems
Computers and Operations Research
The open vehicle routing problem: Algorithms, large-scale test problems, and computational results
Computers and Operations Research
A hybrid evolution strategy for the open vehicle routing problem
Computers and Operations Research
An open vehicle routing problem metaheuristic for examining wide solution neighborhoods
Computers and Operations Research
The open vehicle routing problem with fuzzy demands
Expert Systems with Applications: An International Journal
A survey: algorithms simulating bee swarm intelligence
Artificial Intelligence Review
A hybrid honey bees mating optimization algorithm for the probabilistic traveling salesman problem
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
Honey Bees Mating Optimization algorithm for large scale vehicle routing problems
Natural Computing: an international journal
Honey Bees Mating Optimization algorithm for financial classification problems
Applied Soft Computing
Particle swarm optimization for open vehicle routing problem
ICIC'06 Proceedings of the 2006 international conference on Intelligent computing: Part II
Honey bees mating optimization algorithm for the Euclidean traveling salesman problem
Information Sciences: an International Journal
An ant colony system for the open vehicle routing problem
ANTS'06 Proceedings of the 5th international conference on Ant Colony Optimization and Swarm Intelligence
Critical interplay between density-dependent predation and evolution of the selfish herd
Proceedings of the 15th annual conference on Genetic and evolutionary computation
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Honey Bees Mating Optimization algorithm is a relatively new nature inspired algorithm. In this paper, this nature inspired algorithm is used in a hybrid scheme with other metaheuristic algorithms for successfully solving the Open Vehicle Routing Problem. More precisely, the proposed algorithm for the solution of the Open Vehicle Routing Problem, the Honey Bees Mating Optimization (HBMOOVRP), combines a Honey Bees Mating Optimization (HBMO) algorithm and the Expanding Neighborhood Search (ENS) algorithm. Two set of benchmark instances is used in order to test the proposed algorithm. The results obtained for both sets are very satisfactory. More specifically, in the fourteen instances proposed by Christofides, the average quality is 0.35% when a hierarchical objective function is used, where, first, the number of vehicles is minimized and, afterwards, the total travel distance is minimized and the average quality is 0.42% when only the travel distance is minimized, while for the eight instances proposed by Li et al. when a hierarchical objective function is used the average quality is 0.21%.