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نتیجه جستجو - Transportation problem

تعداد مقالات یافته شده: 3
ردیف عنوان نوع
1 Multi-objective sustainable opened- and closed-loop supply chain under mixed uncertainty during COVID-19 pandemic situation
چندین هدف پایدار حلقه بسته و حلقه بسته تحت عدم اطمینان مخلوط در طی وضعیت همه گیر COVID-19-2021
Logistics problems play a significant role in an emergency situation. During and after a critical circumstance (like pandemic COVID-19), it is an important task to active the opened- and closed-loop system through an efficient and resilient supply chain network. This paper considers a multi-objective multi-product multi-period two-stage sustainable opened- and closed-loop supply chain planning to maintain supply among production centers and various hospitals during COVID-19 pandemic situation. To build a less contagious network, transportation problem and pick-up-delivery vehicle routing problem are designed as two stages, respectively to carry out distribution. We allow a mixed uncertain environment by considering uncertain-random parameters in the proposed model to express ambiguity in real-life data. A multi-attribute decision making approach is suggested to determine the priorities of affected areas, according to their urgency in terms of entropy weights. Moreover, a robust optimization approach for uncertain-random parameter is developed to cope with uncertainty in different scenarios, and thereafter augmented weighted Tchebycheff method is applied to solve the model. To demonstrate the practicability of the proposed model and solving approach, three test problems with reasonable sizes are considered and results are discussed through some sensitivity analyses.
Keywords: Sustainable opened- and closed-loop supply chain | Mixed uncertainty | Multi-attribute decision making | Transportation problem | Pick-up-delivery vehicle routing problem | Robust optimization.
مقاله انگلیسی
2 Transportation problems for intermodal networks: Mathematical models, exact and heuristic algorithms, and machine learning
مشکلات حمل و نقل برای شبکه های intermodal: مدل های ریاضی ، الگوریتم های دقیق و اکتشافی ، و یادگیری ماشین-2019
This paper presents a combinatorial problem called a pick-up routing problem with a three-dimensional (3D-PRP) loading constraint, clustered backhauls at the operational level, and train loading at the tactical level for an intermodal transportation network. A two-phase approach, called clustering first, packing- routing second, is proposed for use during the first stage. The clustering of backhauls is carried out using the k-means algorithm. A hybrid approach is provided, which combines the packing of orders by first solving a 3D loading problem for each cluster using machine learning with a best-fit-first strategy, with routing using a genetic algorithm. During the second stage, the train-loading problem is solved using a mixed integer programming approach to minimise the total costs by incorporating various cost types, in which detention and demurrage costs are taken into account. All solution approaches are computationally evaluated on real-world data provided by an international logistics firm and new randomly generated instances. Comparisons are carried out using both exact solution methods and heuristic approaches, and the proposed approach was shown to be more effective for real-world problems.
Keywords: Intermodal transportation | Pick-up routing with three-dimensional | loading | Train loading | Heuristic approach | Mathematical model, Machine learning
مقاله انگلیسی
3 Impacts of Motorcycle Demand Management in Yangon, Myanmar
اثرات مدیریت تقاضای موتور سیکلت در یانگون، میانمار-2017
This study analyzes the potential impacts of motorcycle demand management and its contribution to the transportation market in Yangon, Myanmar, where motorcycles have been banned since 2003. A vehicle ownership model with travel demand models of modal choice, destination choice, and trip frequency is estimated using a dataset comprising 8,289 households and 24,373 trips in Yangon, compiled by the Japan International Cooperation Agency in 2013. Next, a traffic demand forecast system is developed in which a traffic assignment model is integrated with a vehicle ownership model and travel demand models to evaluate the impacts of the motorcycle ban. Then, the expected impacts of the motorcycle ban are estimated by comparing multiple scenarios for 2013 and 2035. The results show that the ban could reduce traffic volume and vehicle kilometers traveled by approximately 18.0% and 26.9% in 2013, but only 4.5% and 6.0% in 2035. In other words, the ban significantly contributes to the mitigation of the current urban transportation problems; however, it would promote car ownership and the substitution of motorcycles in line with income growth, wiping out the effects of reduced motorcycle trips in the future. These findings suggest that developing cities should consider the long-term dynamics of motorcycle demand management.
Keywords: motorcycle ban | urban travel demand | developing city | Yangon
مقاله انگلیسی
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