Reliable vehicle routing problem in stochastic networks with correlated travel times

Rajabi-Bahaabadi, Mojtaba; Mohaymany, Afshin Shariat; Babaei, Mohsen; Vigo, Daniele

doi:10.1007/s12351-019-00452-w

Cited by 13 publications

(3 citation statements)

References 62 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…There is a large body of research on the vehicle routing problem with stochastic travel times, which is related to our problem, since travel times of robots are stochastic due to varying presence of obstacles. We refer the reader to Rajabi-Bahaabadi et al (2019) for an overview of existing research on conventional stochastic vehicle routing problems. Among other approaches, stochastic travel times have been modeled with Gamma distributions (Russell and Urban, 2008;Ehmke et al, 2015), and they are important for accurate congestion modeling.…”

Section: Vehicle Routing Problem and Traffic Congestionmentioning

confidence: 99%

Robot-Based Last-Mile Deliveries With Pedestrian Zones

Bakach

Campbell

Ehmke

2022

Front. Future Transp.

View full text Add to dashboard Cite

Since delivery robots share sidewalks with pedestrians, it may be beneficial to choose paths for them that avoid zones with high pedestrian density. In this paper, we investigate a robot-based last-mile delivery problem considering path flexibility given the presence of zones with varying pedestrian level of service (LOS). Pedestrian LOS is a measure of pedestrian flow density. We model this new problem with stochastic travel times and soft customer time windows. The model includes an objective that reflects customer service quality based on early and late arrivals. The heuristic solution approach uses the minimum travel time paths from different LOS zones (path flexibility). We demonstrate that the presence of pedestrian zones leads to alternative path choices in 30% of all cases. In addition, we find that extended time windows may help increase service quality in zones with high pedestrian density by up to 40%.

show abstract

Section: Vehicle Routing Problem and Traffic Congestionmentioning

confidence: 99%

Robot-Based Last-Mile Deliveries With Pedestrian Zones

Bakach

Campbell

Ehmke

2022

Front. Future Transp.

View full text Add to dashboard Cite

show abstract

“…Therefore, most of the research focused on studies using the SPR approach to address the SVRP. For example, Refs [22][23][24] studied the VRP with stochastic customers, stochastic travel time and stochastic demand, respectively, which were modeled as stochastic programming and the corresponding solution algorithms were proposed. However, the above studies did not consider the loading problem, which limited the applicability of these studies to certain scenarios, where each customer consists of a certain number of weighed items with a given width and length.…”

Section: Introductionmentioning

confidence: 99%

An Adaptive Tabu Search Algorithm for Solving the Two-Dimensional Loading Constrained Vehicle Routing Problem with Stochastic Customers

Zhang

2023

Sustainability

View full text Add to dashboard Cite

In practical logistic distributions, uncertainties may exist in each distribution process, and sometimes suppliers have to take undesirable measures to deal with the subsequent schedule variances. In light of the uncertainty of customers in logistics distribution and the widely applied two-dimensional loading patterns in transportation, we propose and formulate a two-dimensional loading-constrained vehicle routing problem with stochastic customers (2L-VRPSC), where each customer has a known probability of presence and customers’ demands are a set of non-stackable items. A stochastic modeling platform of 2L-VRPSC is established based on a Monte Carlo simulation and scenario analysis to minimize the expected total transportation cost. To achieve this, an enhanced adaptive tabu search (EATS) algorithm incorporating the multi-order bottom-fill-skyline (MOBFS) packing heuristic is proposed, where the EATS algorithm searches for the optimal routing combination and the MOBFS checks the feasibility of each route and guides the EATS to search for feasible solutions. The widely used two-dimensional loading-constrained vehicle routing problem (2L-VRP) benchmarks under different loading configurations considering items’ sequential and rotation constraints are applied for experiments, which demonstrates the comparable efficiency of the proposed EATS-MOBFS for solving 2L-VRP. Furthermore, the results and analysis of experiments based on the new 2L-VRPSC instances verify the versatility of the proposed solving approach, which is capable of providing more practical solutions to some real-life scenarios with customers’ uncertain information.

show abstract

“…Scholars at home and abroad have conducted many studies on the VRP. Rajabi-Bahaabadi et al constrained the time window in the model, punishing both early and late arrival, and finally solving the problem by combining the ant colony algorithm (ACO) with tabu search algorithm [20]. Xu H et al proposed an ant colony optimization model combining the improved K-mean and cross operation to solve the dynamic VRP problem.…”

Section: Introductionmentioning

confidence: 99%

Research on e-Commerce Distribution Optimization of Rice Agricultural Products Based on Consumer Satisfaction

et al. 2021

View full text Add to dashboard Cite

With the continuous development of agricultural product e-commerce platforms and the rapid growth of trading volume, conducting in-depth mining and analysis of online review data to improve consumer satisfaction is of considerable importance. This paper uses JingDong's self-run online reviews of rice agricultural products as the research object and analyzes the logistics factors that affect consumer satisfaction through text mining technology. A multi-objective model for logistics center distribution path optimization under a soft time window was constructed. The model used the results of online review analysis, namely, packaging integrity, delivery timeliness, and logistics cost, as the goals, and the model used ant colony algorithm (ACO) and genetic algorithm (GA) to solve the optimal distribution solution to minimize the penalty cost and transportation cost. Through examples to solve the optimal distribution vehicle number and shipping routes, in addition, a comparison of the two types of algorithm performance of the model under different node number indicated that the number of nodes affects algorithm performance. With a node number below 50, the ant ACO has high precision and a better distribution path. With a node number above 50, GA has more comprehensive performance. The average efficiency of the GA is 12.28% higher than that of ACO.

show abstract

Reliable vehicle routing problem in stochastic networks with correlated travel times

Cited by 13 publications

References 62 publications

Robot-Based Last-Mile Deliveries With Pedestrian Zones

Robot-Based Last-Mile Deliveries With Pedestrian Zones

An Adaptive Tabu Search Algorithm for Solving the Two-Dimensional Loading Constrained Vehicle Routing Problem with Stochastic Customers

Research on e-Commerce Distribution Optimization of Rice Agricultural Products Based on Consumer Satisfaction

Contact Info

Product

Resources

About