Boosting sustainable development goals: a hybrid metaheuristic approach for the heterogeneous vehicle routing problem with three-dimensional packing constraints and fuel consumption

Rojas-Saavedra, Juan Esteban; Álvarez-Martínez, David; Escobar, John Willmer

doi:10.1007/s10479-023-05533-w

Cited by 3 publications

(2 citation statements)

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“…The authors use experimentation utilizing 15 generated instances ranging from 5 to 20 cities, observing that the model requires 3–8 h to identify optimal solutions as the number of cities increases. Rojas-Saavedra et al [ 25 ] introduce the Heterogeneous Vehicle Routing Problem with Three-Dimensional Packing Constraints and Environmental Impact based on Fuel Consumption (3L-FHFVRP). The author extends the Heterogeneous Vehicle Routing Problem with 3D Loading Constraints (3L-HFVRP) by incorporating fuel consumption as the objective function.…”

Section: Literature Reviewmentioning

confidence: 99%

A three-phase algorithm for the pollution traveling Salesman problem

García-Vasquez,

Linfati,

Escobar

2024

Heliyon

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Section: Literature Reviewmentioning

confidence: 99%

A three-phase algorithm for the pollution traveling Salesman problem

García-Vasquez,

Linfati,

Escobar

2024

Heliyon

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“…Recognize the imbalance of vehicle loads, C. Wang [24] not only strives to minimize the total length of all routes, but also strives to reduce the difference in load allocated to each vehicle, achieving a more efficient and balanced allocation of resources. On the basis of the 3L-CVRP research, the heterogeneous vehicles is studied in literature [25], and the lowest fuel consumption route for vehicle scheduling is realized through a variable neighborhood search meta-heuristic algorithm considering the impact of heterogeneous fleet and fuel consumption on the environment. D. A.…”

Section: A Vehicle Routing Problems Within Urbanmentioning

confidence: 99%

Optimizing Heterogeneous Vehicle Routes for Urban Distribution Considering the Three-Dimensional Bin Packing Problem of Electric Meters

He,

Zhang,

Lin

et al. 2024

IEEE Access

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With the establishment of smart grids, there is a growing demand for metering electric meters in urban areas. Given the diverse sizes and delicate nature of these meters, traditional scheduling solutions are unable to cater to the multifaceted requirements of urban environments, meters loading, and subsequent logistics scheduling. This study presents an intelligent scheduling model for electric meters in an urban context, taking into account various constraints such as urban traffic congestion, three-dimensional packing of metering devices, delivery time windows, and heterogeneous vehicles. To solve this, we design an improved whale optimization algorithm using a hybrid multi-phase heuristic approach (IWOA-HMOHA). Simulation results show that compared with the traditional meter logistics scheduling strategy, the IWOA-HMOHA algorithm reduces the objective function by 5.4%~ 26.1% compared with other similar algorithms. In addition, compared with the traditional first-in-last-out cargo packing method, the vehicle space utilization rate is improved by 12.62%. The proposed models and algorithms demonstrate excellent adaptability to a range of urban constraints, offering valuable insights and a robust framework essential for the development of logistics solutions in urban.INDEX TERMS logistics applications; the three-dimensional bin packing problem; hybrid multi-phase heuristic approach; evolutionary algorithms; difference strategy

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