Optimization of low-carbon multimodal transport paths in an ambiguous demand environment

Ying Shao; Xiao Long Han; Lu Jia Cao

doi:10.1117/12.2684014

14 June 2023 Optimization of low-carbon multimodal transport paths in an ambiguous demand environment

Ying Shao, Xiao Long Han, Lu Jia Cao

Proceedings Volume 12708, 3rd International Conference on Internet of Things and Smart City (IoTSC 2023）; 127082Q (2023) https://doi.org/10.1117/12.2684014
Event: 3rd International Conference on Internet of Things and Smart City (IoTSC 2023）, 2023, Chongqing, China

Abstract

The study of low-carbon multimodal transport path optimization problems considered in a fuzzy demand environment has important theoretical and practical significance in the situation of high-quality development. By analysing the demand uncertainty problem in the transport process, an improved simulated annealing genetic algorithm is designed to solve the model. The impact of various carbon policies on multimodal transport solutions, costs and carbon emissions is analysed through arithmetic examples. The results show that: 1) the improved simulated annealing genetic algorithm is better than the traditional genetic algorithm in terms of time finding and effect finding to achieve the lowest cost and lowest carbon emission; 2) the carbon tax policy is studied through the example and it is found that the carbon tax constraint is relatively lenient and the improper setting of carbon tax will lead to the increase of total cost; the model and algorithm proposed in this paper can provide theoretical support to the policy making departments and multimodal transport enterprises to optimize transport solutions. The model and algorithm proposed in this paper can provide a theoretical basis for policy making authorities and multimodal transport enterprises to optimize transport solutions.

Citation Download Citation

Ying Shao, Xiao Long Han, and Lu Jia Cao "Optimization of low-carbon multimodal transport paths in an ambiguous demand environment", Proc. SPIE 12708, 3rd International Conference on Internet of Things and Smart City (IoTSC 2023）, 127082Q (14 June 2023); https://doi.org/10.1117/12.2684014

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