摘要
多式联运计划制定的超前性及货物需求的不确定性会导致转运时间动态变化,基于此,考虑转运时间与运输需求动态相关,构建总运输成本和总运输时间最低的多目标模型并利用线性加权法将多目标转换为单目标。依据机会约束规划理论将模型清晰化,设计基于模拟退火的遗传算法求解,最后进行算例分析验证模型的可行性。结果表明:满足最优运输方案的运能下限时,随着不确定货运量分布区间的增加,转运时间在总运输时间中的占比逐渐提升,但不影响运输方案的选择,多式联运经营人可根据以往经验选择最优方案;在不确定货运量分布区间超过最优运输方案的运能下限时,运输方案会发生改变,铁路占比逐渐提升,转运时间占比逐渐降低直至为0,此时多式联运经营人制订运输方案时可以通过提高铁路占比减少转运次数以降本增效,验证了所提出算法的可行性与优越性。
Based on the dynamic change of transit time caused by advanced development of multimodal transport plans and the uncertainty of cargo demand,a multi-objective model with the lowest total transportation cost and total transit time was constructed,and multi-objective was converted to single-objective by linear weighting,considering the dynamic correlation between transit time and transportation demand.The model was clarified according to the chance constraint programming theory,and a genetic algorithm based on simulated annealing was designed to solve the problem.Finally,the feasibility of the model was verified by an example analysis.Results showed that when the lower limit of the optimal transportation plan was satisfied,the proportion of transport time in the total transport time gradually increased with the increase of the uncertain distribution range of freight volume,but it did not affect the choice of transportation scheme.The multimodal transport operator could choose the optimal scheme according to previous experience.When the uncertain distribution range of freight volume exceeded the lower limit of the optimal transport plan,the transportation plan changed,the proportion of railway gradually increased,and the proportion of transport time gradually decreased until it reached 0.At this time,the multimodal transport operator reduced the cost and improved the efficiency by increasing the proportion of railway in the formulation of transport scheme,which verified the feasibility and superiority of the proposed algorithm.
作者
汤瑞
胡军红
闻成维
张雯婕
TANG Rui;HU Junhong;WEN Chengwei;ZHANG Wenjie(College of Transportation Engineering,Nanjing Tech University,Nanjing 211800,China)
出处
《南京工业大学学报（自然科学版）》
CAS
北大核心
2023年第5期554-562,共9页
Journal of Nanjing Tech University(Natural Science Edition)
基金
江苏省研究生科研与实践创新计划(SJCX22_0479)。
关键词
多式联运
路径规划
不确定需求
中转时间
基于模拟退火的遗传算法
multimodal transport
route plan
uncertain demand
transit time
genetic algorithm based on simulated annealing
