Metastrategy simulated annealing and tabu search algorithms for the vehicle routing problem
Annals of Operations Research - Special issue on Tabu search
Cyclic transfer algorithms for multivehicle routing and scheduling problems
Operations Research
A Subpath Ejection Method for the Vehicle Routing Problem
Management Science
A tabu scatter search metaheuristic for the arc routing problem
Computers and Industrial Engineering - Special issue: Focussed issue on applied meta-heuristics
A Template for Scatter Search and Path Relinking
AE '97 Selected Papers from the Third European Conference on Artificial Evolution
A genetic algorithm for the vehicle routing problem
Computers and Operations Research
A Set-Partitioning-Based Heuristic for the Vehicle Routing Problem
INFORMS Journal on Computing
Hybrid particle swarm optimization for vehicle routing problem with time windows
MAMECTIS/NOLASC/CONTROL/WAMUS'11 Proceedings of the 13th WSEAS international conference on mathematical methods, computational techniques and intelligent systems, and 10th WSEAS international conference on non-linear analysis, non-linear systems and chaos, and 7th WSEAS international conference on dynamical systems and control, and 11th WSEAS international conference on Wavelet analysis and multirate systems: recent researches in computational techniques, non-linear systems and control
Fuzzy sliding-mode control for ball and beam system with fuzzy ant colony optimization
Expert Systems with Applications: An International Journal
Software framework for vehicle routing problem with hybrid metaheuristic algorithms
ACC'11/MMACTEE'11 Proceedings of the 13th IASME/WSEAS international conference on Mathematical Methods and Computational Techniques in Electrical Engineering conference on Applied Computing
PREACO: A fast ant colony optimization for codebook generation
Applied Soft Computing
An ant colony algorithm for the multi-compartment vehicle routing problem
Applied Soft Computing
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This paper presents a novel hybrid ant colony optimization approach called SS_ACO algorithm to solve the vehicle routing problem. The main feature of the hybrid algorithm is to hybridize the solution construction mechanism of the ant colony optimization (ACO) with scatter search (SS). In our hybrid algorithm, we use ACO algorithm and greedy heuristic to generate the initial solutions which are then formed the reference set. Within the scatter search framework, after two-solution combination method for the reference set has been applied, we employ ACO method to generate new solutions through updating the common arc pheromone mechanism. Moreover, during implementing the hybrid algorithm, cyclic transfers, a new class of neighborhood search algorithm can also be embedded into the scatter search framework as neighborhood search to improve solutions. Despite the size of the cyclic transfer neighborhood is very large, a restricted subset of the cyclic transfer neighborhood is adopted to reduce the computational requirements to reasonable levels. Finally, the experimental results have shown that the proposed hybrid method is competitive to solve the vehicle routing problem compared with the best existing methods in terms of solution quality.