Bidirectional heterogeneous fleet vehicle routing problem with three-dimensional loading constraints for sales-recycling scenario

In pursuit of sustainable manufacturing and transportation paradigms, enterprises focus on ameliorating transportation costs while enhancing customer satisfaction by integrating forward and reverse logistics. However, existing research on sales-recycling models often overlooks constraints, leading to inaccuracies. This paper addresses this gap by introducing the 3L-MD-HFVRPSPD, a complex optimization challenge based on the Vehicle Routing Problem(VRP), which considers multiple depots, diverse vehicle fleets, dual stacking, simultaneous pick-up and delivery, and 3D loading limitations. A hybrid algorithm is formulated for problem resolution, employing the Non-dominated Sorting Genetic Algorithm-II (NSGA-II) for vehicle routing and the heuristic Residual-Space-Optimized Algorithm (RSO) for load validation. Tests demonstrate that this approach outperforms traditional methods, delivering superior solutions more expeditiously.

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Publication Details

Published
2024-12-20
DOI
https://doi.org/10.1117/12.3054546
Primary Topic
Vehicle Routing Optimization Methods
Type
article
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article

Bidirectional heterogeneous fleet vehicle routing problem with three-dimensional loading constraints for sales-recycling scenario

Liya Yao, Shuzhu Zhang, Zhaoqi Wang
Vehicle Routing Optimization Methods
article

Bidirectional heterogeneous fleet vehicle routing problem with three-dimensional loading constraints for sales-recycling scenario

Liya Yao, Shuzhu Zhang, Zhaoqi Wang
article en

Abstract

In pursuit of sustainable manufacturing and transportation paradigms, enterprises focus on ameliorating transportation costs while enhancing customer satisfaction by integrating forward and reverse logistics. However, existing research on sales-recycling models often overlooks constraints, leading to inaccuracies. This paper addresses this gap by introducing the 3L-MD-HFVRPSPD, a complex optimization challenge based on the Vehicle Routing Problem(VRP), which considers multiple depots, diverse vehicle fleets, dual stacking, simultaneous pick-up and delivery, and 3D loading limitations. A hybrid algorithm is formulated for problem resolution, employing the Non-dominated Sorting Genetic Algorithm-II (NSGA-II) for vehicle routing and the heuristic Residual-Space-Optimized Algorithm (RSO) for load validation. Tests demonstrate that this approach outperforms traditional methods, delivering superior solutions more expeditiously.

Beijing Institute of Technology (CN)
Openalex Percentile: Top 65%
Vehicle Routing Optimization Methods
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