Low-Carbon Multimodal Transportation Path Optimization under Dual Uncertainty of Demand and Time

نویسندگان

چکیده

The research on the optimization of a low-carbon multimodal transportation path under uncertainty can have an important theoretical and practical significance in high-quality development situation. This paper investigates problem dual uncertainty. A hybrid robust stochastic (HRSO) model is established considering cost, time cost carbon emission cost. In order to solve this problem, catastrophic adaptive genetic algorithm (CA-GA) based Monte Carlo sampling designed tested for validity. schemes costs different modes are compared, impacts uncertain parameters analyzed by 15-node network numerical example. results show that: (1) mode will affect decision-making transportation, including route mode; (2) with demand increase total due pursuit stability; (3) influence significant fuzzy, showing trend irregular wave-shaped change, like ups downs mountains. we proposed provide basis administrative department logistic services providers optimize scheme

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ژورنال

عنوان ژورنال: Sustainability

سال: 2021

ISSN: ['2071-1050']

DOI: https://doi.org/10.3390/su13158180