Ant Colony System for Optimizing Vehicle Routing Problem with Time Windows
CIMCA '05 Proceedings of the International Conference on Computational Intelligence for Modelling, Control and Automation and International Conference on Intelligent Agents, Web Technologies and Internet Commerce Vol-2 (CIMCA-IAWTIC'06) - Volume 02
A cooperative strategy for a vehicle routing problem with pickup and delivery time windows
Computers and Industrial Engineering
Scheduling: Theory, Algorithms, and Systems
Scheduling: Theory, Algorithms, and Systems
Multiple Ant Colony Optimization for a Rich Vehicle Routing Problem: A Case Study
KES '07 Knowledge-Based Intelligent Information and Engineering Systems and the XVII Italian Workshop on Neural Networks on Proceedings of the 11th International Conference
Proceedings of the 40th Conference on Winter Simulation
An ant colony system (ACS) for vehicle routing problem with simultaneous delivery and pickup
Computers and Operations Research
KES'06 Proceedings of the 10th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part I
iCoMAS: an agent-based system for cooperative transportation planning in the food industry
HoloMAS'11 Proceedings of the 5th international conference on Industrial applications of holonic and multi-agent systems for manufacturing
| Hi-index | 0.00 |
In this paper, we suggest efficient heuristics to solve a cooperative transportation planning problem that is motivated by a scenario found in the German food industry. After an appropriate decomposition of the entire problem into sub problems, we obtain a set of rich vehicle routing problems (VRP) including due dates for the delivery of the orders, capacity constraints and maximum operating time window constraints for the vehicles, and outsourcing options. Each of these sub problems is solved by a greedy heuristic that takes the distance of the locations of customers and the time window constraints into account. The greedy heuristic is further improved by applying an Ant Colony System (ACS). The suggested heuristics are assessed in a rolling horizon setting using discrete event simulation. The results of some preliminary computational experiments are provided. We show that the ACS based heuristic outperforms the greedy heuristic.