A hybrid algorithm for the vehicle routing problem with three-dimensional loading constraints and mixed backhauls

Koch, Henriette; Schlögell, Maximilian; Bortfeldt, Andreas

doi:10.1007/s10951-019-00625-7

Cited by 16 publications

(2 citation statements)

References 41 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Reference [35] focused on the split delivery vehicle routing problem with three-dimensional loading constraints combining vehicle routing (3L-SDVRP) with a proposed hybrid algorithm consisting of a local search algorithm for routing and a genetic algorithm and several construction heuristics for packing. Reference [36] investigated a vehicle routing problem with three-dimensional loading constraints and mixed backhauls (3L-VRPMB) and proposed a hybrid metaheuristic consisting of a reactive tabu search for the routing problem and different packing heuristics for the loading problem. Reference [37] proposed a new integrated model to incorporate both the three-dimensional and time window aspects of the routing problem (3L-CVRPTW), developing a two-stage algorithm solve it.…”

Section: Related Workmentioning

confidence: 99%

A Double Traveling Salesman Problem With Three-Dimensional Loading Constraints for Bulky Item Delivery

et al. 2021

View full text Add to dashboard Cite

This article considers bulky item delivery problems in which multiple items are retrieved and loaded onto a vehicle from different warehouses and then delivered. This problem is described as a double traveling salesman problem with three-dimensional container loading constraints with multiple stacks. The double TSP with multiple stacks is used to determining the shortest route performing pickups and deliveries in two separated networks (one for pickups and one for deliveries) using only one container. Repacking is not allowed after loading the items into the container. An integer linear programming model is proposed to solve this problem, a standard genetic algorithm and an improved genetic algorithm is designed. In the improved genetic algorithm, a Lin-Kernighan algorithm is used to improve the delivery route, a k-means clustering algorithm, and a heuristic packing scheme improvement rules work together to improve the loading route. The results show that the improved genetic algorithm is superior to the standard genetic algorithm in large scale problems.INDEX TERMS Double traveling salesman problem, three-dimensional container loading, bulky item delivery, genetic algorithm.

show abstract

Section: Related Workmentioning

confidence: 99%

A Double Traveling Salesman Problem With Three-Dimensional Loading Constraints for Bulky Item Delivery

et al. 2021

View full text Add to dashboard Cite

show abstract

“…Recently, a simulated annealing method [12] was proposed for solving four classes of 2L-VRP, which improved loads of best-known solutions. Thus far, a large number of extended 2L-VRPs have received research attention, e.g., 2L-VRP with backhauls [13], 2L-VRP with heterogeneous fleet [14,15], 2L-VRP with split delivery [16] and three-dimensional constrained vehicle routing problem [17][18][19]. Nevertheless, the above research generally considers that the geographic location, demand, central depot, vehicle driving status and other information of customers are known in advance and do not change.…”

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

Vehicle Routing Problems with Loading Constraints: An Overview of Variants and Solution Methods

Sbai

Krichen

2022

Optimization and Machine Learning

View full text Add to dashboard Cite

A hybrid algorithm for the vehicle routing problem with three-dimensional loading constraints and mixed backhauls

Cited by 16 publications

References 41 publications

A Double Traveling Salesman Problem With Three-Dimensional Loading Constraints for Bulky Item Delivery

A Double Traveling Salesman Problem With Three-Dimensional Loading Constraints for Bulky Item Delivery

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

Vehicle Routing Problems with Loading Constraints: An Overview of Variants and Solution Methods

Contact Info

Product

Resources

About