VRP variants applicable to collecting donations and similar problems: A taxonomic review

Gutiérrez-Sánchez, Alexander; Rocha-Medina, Linda Bibiana

doi:10.1016/j.cie.2021.107887

Cited by 19 publications

(7 citation statements)

References 125 publications

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“…The ship speed optimization problem with a time window refers to a more complex class of VRP problems in which not only the quantity of cargo demanded by each customer should be considered when developing a transportation route and cargo ships should not be overloaded, but also the requirements of each customer for cargo reception time [19].…”

Section: Modeling Of Cw Saving Algorithm With Time Windowsmentioning

confidence: 99%

Speed optimization of inland sea vessels based on C.W saving algorithm

Liu

2023

Applied Mathematics and Nonlinear Sciences

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This paper constructs a mathematical model of the C-W saving algorithm based on the characteristics of the C-W saving algorithm and the collection and data analysis of energy efficiency data of ships without time window constraints. On this basis, the mathematical model with the time window constraint is further constructed by adding the time window constraint and fully considering some factors in the transportation of inland vessels that cannot be ignored, such as fuel price, carbon tax price and sailing speed. Finally, the impact of fuel, charter, and carbon tax prices on the optimization scheme is analyzed by the sensitivity analysis method. With the lowest total sailing cost as the target, the total sailing cost of the whole voyage is reduced by $4,749, which is 3.75% less than last year. Optimization with the lowest carbon emission as the goal, the whole voyage CO2 emissions reduced by 4.22t, a year-on-year reduction of 10.76%. Considering the total voyage cost and carbon emission for multi-objective optimization, the total voyage cost is reduced by 1210, which is 0.91% less than the same period last year. Therefore, the speed optimization method for inland sea vessels based on the C-W saving algorithm can provide a basis for shipowners and speed companies in making sailing plans.

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Section: Modeling Of Cw Saving Algorithm With Time Windowsmentioning

confidence: 99%

Speed optimization of inland sea vessels based on C.W saving algorithm

Liu

2023

Applied Mathematics and Nonlinear Sciences

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“…Hence, it is important to clarify how to arrange a special vehicle, that is, select feasible nodes from all massive-cargo transportation nodes and determine the order of the vehicle visiting these nodes, so as to transport massive cargos from the origin to the destination. Without loss of generality, the model assumes that: (1) The random interference of the traffic network and the impact of the time window of massive cargos on massive-cargo transportation routes are not considered; (2) The conflicts between multiple massive-cargo logistics transportation routes are ignored; (3) The throughput capacity information of massivecargo transportation networks is obtained in advance. According to the problem description, the symbols and definitions of relevant variables are shown in Table 1, and the mathematical model is established as follows.…”

Section: Massive-cargo Logistics Transportation Routing Modelmentioning

confidence: 99%

“…Previous studies of vehicle routes focused on the related problems considering vehicle constraints and related problem variants [1]. Leng et al [2] established a mathematical model for the vehicle routing problem of multiple distribution centers based on the logistics distribution system of urban rail transit and proposed a new concentration immune algorithm-based particle swarm algorithm to solve the vehicle routing problem by combining the concept of antibody concentration.…”

Section: Introductionmentioning

confidence: 99%

A Massive-Cargo Transportation Routing Model Based on Reinforcement Learning

Wei

2022

Frontiers in Artificial Intelligence and Applications

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Considering the size (length, width, and height) and weight of massive cargos and on the basis of satisfying the throughput capacity of the road network, a massive-cargo transportation routing model was proposed to find the shortest transportation route based on the origin and destination. According to the characteristics of the routing problem, a reinforcement learning algorithm was designed to solve the problem and determine the strategy, reward function, value function, and environment model. Additionally, based on a case study, an optimized transportation plan was developed and the model sensitivity was analyzed to verify the validity and correctness of the proposed model and algorithm.

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“…The VRP and its more complex variations are constantly being studied by the research community as more variants are emerging in recent years. Additional information can be read in the following works: [15][16][17][18].…”

Section: The Vehicle Routing Problemmentioning

confidence: 99%

A Review of the Vehicle Routing Problem and the Current Routing Services in Smart Cities

et al. 2022

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In this survey, the issues of urban routing are analyzed, and critical considerations for smart and cost-effective delivery services are highlighted. Smart cities require intelligent services and solutions to address their routing issues. This article gives a brief description of current services that either apply classical methods or services that employ machine learning approaches. Furthermore, a comparison of the most promising research options in regard to VRP is provided. Finally, an initial design of a holistic scheme that would optimally combine several tools and approaches to serve the needs of different users with regard to the VRP is presented.

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VRP variants applicable to collecting donations and similar problems: A taxonomic review

Cited by 19 publications

References 125 publications

Speed optimization of inland sea vessels based on C.W saving algorithm

Speed optimization of inland sea vessels based on C.W saving algorithm

A Massive-Cargo Transportation Routing Model Based on Reinforcement Learning

A Review of the Vehicle Routing Problem and the Current Routing Services in Smart Cities

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