Multi-modal cargo logistics distribution problem: Decomposition of the stochastic risk-averse models

Mohammadi, Mahsa; Shahparvari, Shahrooz; Soleimani, Hamed

doi:10.1016/j.cor.2021.105280

Cited by 13 publications

(3 citation statements)

References 61 publications

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“…Based on the existing research results of logistics distribution vehicle scheduling theory, this paper will use technical means to study logistics distribution vehicle scheduling decision-making methods and provide new technologies and methods for logistics distribution business decision-making management. (1) The concept of logistics distribution [7]: logistics distribution refers to the logistics in which goods are sorted, packaged, divided, and assembled according to the needs of customers in a certain economic and reasonable area and arrived at the designated place in time. It is a link connected with important direct consumers in logistics activities.…”

Section: Introductionmentioning

confidence: 99%

Research on Emergency Logistics Vehicle Route Scheduling and Optimization Method Based on Multi-Intelligent Decision System

Liang

2022

Journal of Sensors

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Logistics distribution vehicle planning is an important issue in logistics transportation activities, and it is also a research hotspot in theoretical circles at home and abroad. At present, many studies have focused on establishing vehicle planning models and optimizing vehicle planning in different environments and have achieved rich results. As an important part of transportation production process, the efficiency of logistics distribution is very important to the whole production process. Especially for emergency logistics, every minute is very critical for emergency situations such as disaster relief. In order to improve the efficiency of emergency logistics, this paper applies multiagent technology to emergency logistics and puts forward an integrated modeling method of enterprise macromodeling, business process mesomodeling, and micromodel design. Using the agent-oriented system development method, an emergency logistics distribution vehicle planning model system is established. The development process of multiagent automatic trading system is described. The results show that it is feasible and effective to use multi-intelligent fuselage technology for emergency logistics distribution vehicle planning and decision-making. The algorithm proposed in this paper has advantages over the container order sequence processing scheme, and the total cost of order acceptance decreases sharply in the initial stage, which shows the practical convergence of the algorithm. The adjacency search method and Tabu search method deal with the calculation of total labor cost, and the Tabu neighborhood search algorithm obtains better results with lower labor cost.

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Section: Introductionmentioning

confidence: 99%

Research on Emergency Logistics Vehicle Route Scheduling and Optimization Method Based on Multi-Intelligent Decision System

Liang

2022

Journal of Sensors

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“…This paper adopts the transposed form of the matrix. The matrix shows the relative values of 36 samples on eight indexes [19][20][21]. The related data of the transpose matrix are as follows:…”

Section: Estimation Of Urban Logistics Capacity Based On Fuzzymentioning

confidence: 99%

Research on the Measurement of Logistics Capability of Core Cities along “the Belt and Road” in China

Sun

Wang

Xiao

et al. 2022

Advances in Mathematical Physics

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The B&R strategy came into being to promote the free and orderly flow of economic factors, the efficient allocation of resources, and the depth of market integration. Logistics is the artery of element circulation and the basis of the B&R. The logistics capacity of core cities along the R&B will be an essential factor affecting the strategy. In this context, it is of practical significance to measure the logistics capacity of the core cities along the B&R. Since combing domestic and overseas research, this paper first uses clustering analysis to screen out nine core cities along the B&R and then uses fuzzy matter-element analysis to measure their urban logistics capacity and sort them. The results show that the urban logistics capacity in the eastern coastal areas of China is higher than that in northwest and southwest China. The logistics capacity of cities along “The 21st Century Sea Silk Road” is more robust than that of others and through the urban agglomeration could further achieve economies of scale. The logistics capacity of cities along the “Silk Road Economic Zone” should improve the construction of logistics infrastructure and enhance logistics information in the future.

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“…The multimodal model has been used to select alternative routes using various factors such as transportation cost, transfer cost, transit time, transportation distance, document fees, port congestion surcharges, customs fees, and trust index in research [3]. The work in [4] aims to develop a solution framework for large-scale planning problems through a novel multimodal stochastic model to help decision-makers to create a desirable plan for China-Europe routes. The research streams on deterministic and stochastic models for multimodal transportation (including uncertain demand, transportation time, cost, and capacity) are compared in [1].…”

Section: Review Of Recent Literaturementioning

confidence: 99%

Selecting a Rational Scheme of Delivery by Road Transport: A Case Study of Goods Deliveries from China to Russia through Kazakhstan

et al. 2022

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Road transport is in most cases the only available transport option in rural regions with undeveloped railway infrastructure. The problem of choosing the structure of the logistics chain is one of the most important ones that forwarding companies must solve when planning freight transportation. Due to political peculiarities, transportation of goods by road through the territory of Kazakhstan must be carried out by national forwarders, which results in centralizing the decision-making process and shifting the tasks of designing the structure of supply chains to the Kazakh forwarding companies. In this paper, we develop a mathematical model to solve the problem of choosing the right structure for a logistics chain. The proposed model considers the existing legal constraints in the region. Based on a simulated demand for cargo deliveries from China to Russia, we use a numerical example to show how to justify the structure of the logistics chain characterized by minimal total costs of the companies involved in the delivery process.

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Multi-modal cargo logistics distribution problem: Decomposition of the stochastic risk-averse models

Cited by 13 publications

References 61 publications

Research on Emergency Logistics Vehicle Route Scheduling and Optimization Method Based on Multi-Intelligent Decision System

Research on Emergency Logistics Vehicle Route Scheduling and Optimization Method Based on Multi-Intelligent Decision System

Research on the Measurement of Logistics Capability of Core Cities along “the Belt and Road” in China

Selecting a Rational Scheme of Delivery by Road Transport: A Case Study of Goods Deliveries from China to Russia through Kazakhstan

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