Multi-Objective Optimization of Short-Inverted Transport Scheduling Strategy Based on Road–Railway Intermodal Transport

Dudu Guo, Yinuo Su (), Xiaojiang Zhang, Zhen Yang and Pengbin Duan
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Dudu Guo: School of Transportation Engineering, Xinjiang University, Urumqi 830017, China
Yinuo Su: School of Business, Xinjiang University, Urumqi 830017, China
Xiaojiang Zhang: Xinjiang Xinte Energy Logistics Co., Urumqi 830017, China
Zhen Yang: Xinjiang Hualing Logistics & Distribution Co., Urumqi 830017, China
Pengbin Duan: School of Business, Xinjiang University, Urumqi 830017, China

Sustainability, 2024, vol. 16, issue 15, 1-25

Abstract: This study focuses on the ‘short-inverted transportation’ scenario of intermodal transport. It proposes a vehicle unloading reservation mechanism to optimize the point-of-demand scheduling system for the inefficiency of transport due to the complexity and uncertainty of the scheduling strategy. This paper establishes a scheduling strategy optimization model to minimize the cost of short backhaul and obtain the shortest delivery time window and designs a hybrid NSGWO algorithm suitable for multi-objective optimization to solve the problem. The algorithm incorporates the Non-dominated Sorting Genetic Algorithm II (NSGA-II) algorithm based on the Grey Wolf Optimizer (GWO) algorithm, compensating for a single algorithm’s premature convergence. The experiment selects a logistics carrier’s actual road–rail intermodal short-inverted data and compares and verifies the above data. The results show that the scheduling scheme obtained by this algorithm can save 41.01% of the transport cost and shorten the total delivery time by 46.94% compared with the original scheme, which can effectively protect the enterprise’s economic benefits while achieving timely delivery. At the same time, the optimized scheduling plan resulted in a lower number of transport vehicles, which positively impacted the sustainability of green logistics.

Keywords: road–rail intermodal transport; short-inverted transport; scheduling strategy; multi-objective optimization (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2024
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