A machine learning-based adaptive heuristic for vessel scheduling problem under uncertainty via chance-constrained programming

Efficient vessel scheduling in port is critical for enhancing navigational efficiency. However, it faces substantial challenges due to unforeseeable events. In this context, this paper addresses the vessel scheduling problem with stochastic sailing times in port. The problem is formulated into a cha...

Celý popis

Podrobná bibliografia

Vydané v:	Computers & electrical engineering Ročník 119; s. 109523
Hlavní autori:	Li, Runfo, Zhang, Xinyu, Wang, Chengbo, Cui, Jinlong, Mu, Mengfeng
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Elsevier Ltd 01.10.2024
Predmet:	Adaptive differential evolution algorithm Chance-constrained programming Machine learning Stochastic sailing times Vessel scheduling Adaptive differential evolution algorithm Chance-constrained programming Vessel scheduling Stochastic sailing times Machine learning
ISSN:	0045-7906
On-line prístup:	Získať plný text
Tagy:	Pridať tag Žiadne tagy, Buďte prvý, kto otaguje tento záznam!