An Improved Nutcracker Optimization Algorithm for Valuables Transportation Routing Problem Under Uncertainty

Valuables transportation is often subject to the risk of armed robbery and assault due to its unique characteristics. It remains a challenging problem to maintain security and minimize costs and carbon emissions during transportation. In this paper, the route planning of valuables transportation is...

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Bibliographic Details
Published in:Chinese Control Conference pp. 1896 - 1901
Main Authors: Liu, Yiwei, Hua, Changchun
Format: Conference Proceeding
Language:English
Published: Technical Committee on Control Theory, Chinese Association of Automation 28.07.2025
Subjects:
Accuracy
Carbon dioxide
Convergence
Costs
Nutcracker optimization algorithm
Planning
Risk
Robust optimization
Routing
Security
Transportation
Uncertainty
Vehicle routing
Vehicle routing problem
ISSN:1934-1768
Online Access:Get full text
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Summary:Valuables transportation is often subject to the risk of armed robbery and assault due to its unique characteristics. It remains a challenging problem to maintain security and minimize costs and carbon emissions during transportation. In this paper, the route planning of valuables transportation is conceptualized as a multi-objective green vehicle routing problem (VTVRP), which takes robbery probability, transportation costs, and carbon emissions into account. Furthermore, the uncertain variables of carbon emission coefficients and robbery probability are addressed using a robust optimization method. To effectively solve the VTVRP, we develop an improved nutcracker optimization algorithm (INOA). The INOA introduces an adaptive weight mechanism to improve convergence accuracy and embeds a differential evolution operator based on Lévy flight to enhance exploration capabilities. Consequently, the proposed algorithm can obtain a more accurate solution with a faster convergence rate. The effectiveness of the proposed method is investigated through a case study of cash transportation. The results show that the proposed algorithm outperforms other advanced algorithms in solving VTVRP.
ISSN:1934-1768
DOI:10.23919/CCC64809.2025.11179550