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| Content Provider | Springer Nature Link |
|---|---|
| Author | Yang, Zhiwei Osta, Jan Paul Veen, Barry Krevelen, Rick Klaveren, Richard Stam, Andries Kok, Joost Bäck, Thomas Emmerich, Michael |
| Copyright Year | 2016 |
| Abstract | The vehicle routing problem is a classical combinatorial optimization problem. This work is about a variant of the vehicle routing problem with dynamically changing orders and time windows. In real-world applications often the demands change during operation time. New orders occur and others are canceled. In this case new schedules need to be generated on-the-fly. Online optimization algorithms for dynamical vehicle routing address this problem but so far they do not consider time windows. Moreover, to match the scenarios found in real-world problems adaptations of benchmarks are required. In this paper, a practical problem is modeled based on the procedure of daily routing of a delivery company. New orders by customers are introduced dynamically during the working day and need to be integrated into the schedule. A multiple ant colony algorithm combined with powerful local search procedures is proposed to solve the dynamic vehicle routing problem with time windows. The performance is tested on a new benchmark based on simulations of a working day. The problems are taken from Solomon’s benchmarks but a certain percentage of the orders are only revealed to the algorithm during operation time. Different versions of the MACS algorithm are tested and a high performing variant is identified. Finally, the algorithm is tested in situ: In a field study, the algorithm schedules a fleet of cars for a surveillance company. We compare the performance of the algorithm to that of the procedure used by the company and we summarize insights gained from the implementation of the real-world study. The results show that the multiple ant colony algorithm can get a much better solution on the academic benchmark problem and also can be integrated in a real-world environment. |
| Starting Page | 119 |
| Ending Page | 134 |
| Page Count | 16 |
| File Format | |
| ISSN | 15677818 |
| Journal | Natural Computing |
| Volume Number | 16 |
| Issue Number | 1 |
| e-ISSN | 15729796 |
| Language | English |
| Publisher | Springer Netherlands |
| Publisher Date | 2016-04-09 |
| Publisher Place | Dordrecht |
| Access Restriction | One Nation One Subscription (ONOS) |
| Subject Keyword | Ant colony optimization Vehicle routing problem Dynamic vehicle routing problem with time windows Pilot study Theory of Computation Evolutionary Biology Processor Architectures Artificial Intelligence (incl. Robotics) Complex Systems |
| Content Type | Text |
| Resource Type | Article |
| Subject | Computer Science Applications |
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