MACS-VRPTW: a multiple ant colony system for vehicle routing problems with time windows
New ideas in optimization
2-Path Cuts for the Vehicle Routing Problem with Time Windows
Transportation Science
Low Cost Parallel Solutions for the VRPTW Optimization Problem
ICPPW '01 Proceedings of the 2001 International Conference on Parallel Processing Workshops
A Smoothed Dynamic Tabu Search Embedded GRASP for m-VRPTW
ICTAI '04 Proceedings of the 16th IEEE International Conference on Tools with Artificial Intelligence
How to Deal with the VRPTW by using Multi-Agent Coalitions
HIS '04 Proceedings of the Fourth International Conference on Hybrid Intelligent Systems
The Shortest-Path Problem with Resource Constraints and k-Cycle Elimination for k ≥ 3
INFORMS Journal on Computing
Ant colony system: a cooperative learning approach to the traveling salesman problem
IEEE Transactions on Evolutionary Computation
A constructive approach for finding arbitrary roots of polynomials by neural networks
IEEE Transactions on Neural Networks
Zeroing polynomials using modified constrained neural network approach
IEEE Transactions on Neural Networks
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Research on the optimization of Vehicle Routing Problem with Time Windows (VRPTW) is a significant investigation area of ant colony system (ACS). This paper proposes an enhanced ACS, which embeds the sequential insertion heuristic method, to solve VRPTW. The main idea is to organize two respective ant colonies to successively achieve a multiple objective minimization. Experiments on a series of benchmark problems demonstrate the excellent performance of ACS when compared with other optimization methods.