Review of Material Distribution Route Optimization
DOI:
https://doi.org/10.54097/8kjb8q97Keywords:
Material distribution, Path optimization, Multi-objectiveAbstract
The optimization of material distribution routes is an important research field, aiming to enhance the efficiency and accuracy of material distribution by optimizing the distribution routes. This paper provides a review of the research on the optimization of material distribution routes. Firstly, it introduces the background and significance of the problem. Then, it describes the problem. Subsequently, it reviews and evaluates the research progress on different types of material distribution route optimization problems. Finally, it summarizes the current research status and existing challenges of the material distribution route optimization problem. Currently, certain achievements have been made in the practical application of the material distribution route optimization problem, but there are still some challenges, such as the efficiency and scalability of algorithms. Future research can further improve existing solutions, explore new algorithms and models to enhance the effectiveness of material distribution route optimization. In conclusion, the optimization of material distribution routes is a significant and challenging research field. By reviewing existing research results and problems, this paper provides references and guidance for further research on the optimization of material distribution routes.
Downloads
References
[1] Molina, J.C.; Salmeron, J.L.; Eguia, I. An ACS-based memetic algorithm for the heterogeneous vehicle routing problem with time windows. Expert Syst. Appl. 2020, 157, 113379.
[2] Bogue, E.T.; Ferreira, H.S.; Noronha, T.F.; Prins, C. A column generation and a post optimization VNS heuristic for the vehicle routing problem with multiple time windows. Optim. Lett. 2020, 16, 79–95.
[3] Jalilvand, M.; Bashiri, M.; Nikzad, E. An effective Progressive Hedging algorithm for the two-layers time window assignment vehicle routing problem in a stochastic environment. Expert Syst. Appl. 2021, 165, 113877.
[4] Tilk, C.; Olkis, K.; Irnich, S. The last-mile vehicle routing problem with delivery options. OR Spectr. 2021, 43, 877–904.
[5] Hoogeboom, M.; Adulyasak, Y.; Dullaert, W.; Jaillet, P. The Robust Vehicle Routing Problem with Time Window Assignments. Transp. Sci. 2021, 55, 395–413.
[6] Ibrahmi A, Bentaher H, Maalej A.Soil-blade orientation effect on tillage forces determined by 3d finite element models [J].Spanish Journal of Agricultural Research, 2014, 12 (4): 941-951.
[7] Fuping Zhu, Tingting Cao. Machine Design & Manufacture, 2023, (01):136-139+144. An Optimization Method of Material Distribution Route in Workshop Based on Time Window Constraints [J].
[8] Qixiang Li, Zhenfeng Li, Xingli Li. Vehicle Routing Optimization based on Multi-objective Hybrid particle swarm Optimization [J]. Journal of Taiyuan University of Science and Technology, 2023, 44(06):540-545.
[9] Jin Xu, Shoujing Zhang, Yueqiang Liu. Optimization of Bidirectional Material Distribution Path in Flexible Manufacturing Workshop Considering Multiple Models [J]. Light Industry Machinery, 2023, 41(01):97-104.
[10] Keskin M, Catay B, Laporte G (2021) A simulation-based heuristic for the electric vehicle routing problem with time windows and stochastic Waiting times at recharging crisis. Comput Oper Res. https://doi.org/10.1016/j.cor.2020.105060
[11] Erdogan S, Miller-Hooks E (2012) A green vehicle routing problem. Transp Res Part E Log Transp Rev 48:100–114. https:// A, doi.org/10.1016/j.tre.2011.08.001
[12] Artmeier Haselmayr J, Leucker M et al (2010) The shortest path problem revisited: optimal routing for electric vehicles. In: 33rd annual German conference on AI, 2010, pp 309–316
[13] Goeke D, Schneider M (2015) Routing a mixed fleet of electric and conventional vehicles. Eur J Oper Res 245: 81–99. https://doi.Org/10.1016/j.jor. 2015.01.049
[14] Xiaoyong Zhu et al. Study on the Optimization of the Material Distribution Path in an Electronic Assembly Manufacturing Company Workshop Based on a Genetic Algorithm Considering Carbon Emissions [J]. Processes, May 2023, 11(5):1500.
[15] Binghai Zhou, and Zhe Zhao. "Multi-Objective Optimization of Electric Vehicle Routing Problem with Battery Swap and Mixed Time Windows". Neural Computing and Applications of 34, 10 (February 5, 2022): 7325-48. https://doi.org/10.1007/s00521-022-06967- 2.
[16] Angeloudis, P., & Bell, M. G. H. (2010). An uncertainty-aware AGV assignment algorithm for automated container terminals. Transportation Research Part E: Logistics and Transportation Review, 46 (3), 354-366. https://doi.org/10.1016/j.tre.2009.09.001
[17] Lei Liu et al. A new knowledge-guided multi-objective optimisation for the multi-AGV dispatching problem in dynamic production environments [J]. International Journal of Production Research, September 2022, 61(17):6030 -- 6051. (in Chinese)
[18] Yu Cao et al. AGV dispatching and bidirectional conflict-free routing problem in automated container terminal [J]. Computers & Industrial Engineering, September 2023, 184:109611.
Downloads
Published
Issue
Section
License

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.







