Discrete Flower Pollination Algorithm to Solve Vehicle Routing Problem with Time Windows
- DOI
- 10.2991/978-94-6463-772-4_18How to use a DOI?
- Keywords
- Metaheuristics; Flower Pollination; Discrete Optimization; Vehicle Routing Problem; Chaotic Maps
- Abstract
Flower Pollination Algorithm (FPA) is a nature-inspired optimization algorithm based on the pollination process of flowers. Originally FPA was created to solve continuous optimization problems. Here FPA was modified to solve discrete problems. In this paper, FPA was modified by adding Chaotic Maps function to present a different strategy in generating solutions. The modified algorithm was used to solve Vehicle Routing Problem with Time Window (VRPTW). Logistic, Iterative, Sine, Tent, and Singer Maps are the types of Chaotic Maps used in the experiment. Small, medium and large datasets were tested. Three algorithms compared here are original FPA, hybrid FPA-Chaotic Maps and Simulated Annealing. To evaluate the performance of the algorithms, we use total distance, running time and Average Relative Percentage Deviation (ARPD). Based on the experiment results, the hybrid FPA - Chaotic Maps produced the best performance, both for total distance and ARPD. The challenge of hybrid FPA - Chaotic Maps is how to improve the running time.
- Copyright
- © 2025 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Yayuk Ismi Rahayu AU - Budi Santosa AU - Erwin Widodo PY - 2025 DA - 2025/07/01 TI - Discrete Flower Pollination Algorithm to Solve Vehicle Routing Problem with Time Windows BT - Proceedings of the 10th International Conference on Science and Technology (ICST 2024) PB - Atlantis Press SP - 188 EP - 197 SN - 2352-5401 UR - https://doi.org/10.2991/978-94-6463-772-4_18 DO - 10.2991/978-94-6463-772-4_18 ID - Rahayu2025 ER -