Ant Colony Optimization solutions for logistic route planning with pick-up and delivery

Eric Hsueh Chan Lu, Ya Wen Yang, Zeal Li Tse Su

研究成果: Conference contribution

7 引文 斯高帕斯(Scopus)

摘要

Online shopping behaviors lead to a large number of goods need to be transported in the real world. Researches on logistics have attracted extensive attentions. One of popular topics is logistic route planning. Although various previous studies have discussed some classical routing problems, real logistic constraints are not considered such as the vehicle capacity, various logistic requirements, etc. Thus, these solutions may not be directly applied to the logistic route planning. In this paper, we propose a novel solution based on Ant Colony Optimization (ACO) to find high quality logistic routes not only meeting real logistic constraints but also taking pick-up and delivery requirements into account. To the best of our knowledge, this is the first work using ACO to plan the logistic routs that considers various logistic requirements, simultaneously. Through extensive experimental evaluations by a semi-real logistic dataset, the proposed ACO-based solution was shown to deliver excellent performance.

原文English
主出版物標題2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016 - Conference Proceedings
發行者Institute of Electrical and Electronics Engineers Inc.
頁面808-813
頁數6
ISBN(電子)9781509018970
DOIs
出版狀態Published - 2017 二月 6
事件2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016 - Budapest, Hungary
持續時間: 2016 十月 92016 十月 12

出版系列

名字2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016 - Conference Proceedings

Other

Other2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016
國家/地區Hungary
城市Budapest
期間16-10-0916-10-12

All Science Journal Classification (ASJC) codes

  • 電腦視覺和模式識別
  • 人工智慧
  • 控制和優化
  • 人機介面

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