A branch-and-cut algorithm for the two-echelon capacitated vehicle routing problem with grouping constraints

Liu, Tian; Luo, Zhixing; Qin, Hu; Lim, Andrew

doi:10.1016/j.ejor.2017.10.017

Cited by 52 publications

(27 citation statements)

References 24 publications

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“…The 2E-VRP involves a two-layered distribution network: In the first level, vans perform deliveries from distribution centers to urban consolidation centers, also called satellites. At the second level, customers' orders are consolidated into small vehicles that can travel along any street in the city center area, such as minivans, electric vans, and cargo bikes, and delivered to the final customers (Liu et al 2018, Dellaert et al 2019, Li et al 2020, Mühlbauer and Fontaine 2021, Perboli et al 2021.…”

Section: Vehicle Routing Problem With Multiple Synchronizationmentioning

confidence: 99%

Van-based robot hybrid pickup and delivery routing problem

Puchinger

Sun

2022

European Journal of Operational Research

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We present a two-echelon van-based robot last-mile pickup and delivery system in urban settings. Robots can visit areas with van access restrictions, such as pedestrianized areas or university campuses. The van stops at parking nodes to drop off and/or pick up its robot, and to replenish its robot and/or swap its robot's battery if needed. Five van/robot pickup and delivery cases are considered, according to the roles the van/robot plays in the process of pickup/delivery and whether the van transports its robot.To model the proposed problem, we introduce a mixed-integer program including time, freight, and energy. We further propose an adaptive large neighborhood search algorithm to solve larger instances and a capacity feasibility test approach for a single route. We then assess the influence of parking node density on model output. A case study based on a realistic city scenario is introduced. A sensitivity analysis is performed on the robot's travel cost and maximum travel distances, and the effect of van no-go areas is studied. Two classical models (two-echelon vehicle routing with hybrid pickup and delivery and parallel van and robot scheduling with hybrid pickup and delivery) are compared with ours, and results show our model is competitive in appropriate scenario settings. We therefore advocate using the two-echelon van-based robot last-mile pickup and delivery system in urban areas.

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Section: Vehicle Routing Problem With Multiple Synchronizationmentioning

confidence: 99%

Van-based robot hybrid pickup and delivery routing problem

Puchinger

Sun

2022

European Journal of Operational Research

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“…This phenomenon enables the application of precise method for studying the collaborative logistics networks with pickups and deliveries. Researchers have studied numerous precise methods [18,19]. Sedeño-Noda and Raith [20] proposed a Dijkstra-like method to determine all extreme supported non-dominated solutions to the shortest path problem.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Zhang et al [22] studied a stochastic network based on lagrangian relaxation method to find a reliable shortest path. Liu et al [18] presented a branch-and-cut algorithm to study the two-echelon capacitated vehicle routing problem. Andrade and Saraiva [23] used shortest path method to solve an inter-linear programming model, which aims to find the shortest path between two vertices.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Constraint (17) ensures that the electro-tricycles' capacity meets the total demand of customers on a delivery route. Constraint (18) guarantees that the total travel time during pickup process does not exceed the maximum route time allowed. Constraint (19) guarantees that the total travel time during delivery process does not exceed the maximum route time allowed.…”

Section: Optimization Model Formulationmentioning

confidence: 99%

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Collaborative Mechanism for Pickup and Delivery Problems with Heterogeneous Vehicles under Time Windows

et al. 2019

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The sustainability and complexity of logistics networks come from the temporally and spatially uneven distributions of freight demand and supply. Operation strategies without considering the sustainability and complexity could dramatically increase the economic and environmental costs of logistics operations. This paper explores how the unevenly distributed demand and supply can be optimally matched through collaborations, and formulates and solves a Collaborative Pickup and Delivery Problem under Time Windows (CPDPTW) to optimize the structures of logistics networks and improve city sustainability and liverability. The CPDPTW is a three-stage framework. First, a multi-objective linear optimization model that minimizes the number of vehicles and the total cost of logistics operation is developed. Second, a composite algorithm consisting of improved k-means clustering, Demand-and-Time-based Dijkstra Algorithm (DTDA) and Improved Non-dominated Sorting Genetic Algorithm-II (INSGA-II) is devised to solve the optimization model. The clustering algorithm helps to identify the feasible initial solution to INSGA-II. Third, a method based on improved Shapley value model is proposed to obtain the collaborative alliance strategy that achieves the optimal profit allocation strategy. The proposed composite algorithm outperforms existing algorithms in minimizing terms of the total cost and number of electro-tricycles. An empirical case of Chongqing is employed to demonstrate the efficiency of the proposed mechanism for achieving optimality for logistics networks and realizing a win-win situation between suppliers and consumers.

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“…For a comprehensive overview of the VRPs, we refer the reader to Toth and Vigo (2002), Golden et al (2008), Eksioglu et al (2009), and Braekers et al (2016). According to the numbers of existing articles in the literature, the most representative VRP variants include the VRP with time windows (Solomon, 1987;Bräysy and Gendreau, 2005a;2005b), location routing problem (Nagy and Salhi, 2007;Prodhon and Prins, 2014;Schneider and Drexl, 2017), dial-a-ride problem (Cordeau and Laporte, 2007;Liu et al, 2015;Ho et al, 2018;Luo et al, 2019), two-echelon capacitated VRP (Perboli et al, 2011;Baldacci et al, 2013;Liu et al, 2018), pickup and delivery problem (Savelsbergh and Sol, 1995;Nagy et al, 2015), arc routing problem (Dror, 2000;Corberán and Prins, 2010;Yu et al, 2019a), periodic vehicle routing problem (Zhang et al, 2013;Campbell and Wilson, 2014;Luo et al, 2015), and split delivery VRP (Desaulniers, 2010;Archetti and Speranza, 2012;Luo et al, 2017).…”

Section: Introductionmentioning

confidence: 99%

A review on the electric vehicle routing problems: Variants and algorithms

Qin

Ren

et al. 2021

Front. Eng. Manag.

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Over the past decade, electric vehicles (EVs) have been considered in a growing number of models and methods for vehicle routing problems (VRPs). This study presents a comprehensive survey of EV routing problems and their many variants. We only consider the problems in which each vehicle may visit multiple vertices and be recharged during the trip. The related literature can be roughly divided into nine classes: Electric traveling salesman problem, green VRP, electric VRP, mixed electric VRP, electric location routing problem, hybrid electric VRP, electric dial-a-ride problem, electric two-echelon VRP, and electric pickup and delivery problem. For each of these nine classes, we focus on reviewing the settings of problem variants and the algorithms used to obtain their solutions.

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A branch-and-cut algorithm for the two-echelon capacitated vehicle routing problem with grouping constraints

Cited by 52 publications

References 24 publications

Van-based robot hybrid pickup and delivery routing problem

Van-based robot hybrid pickup and delivery routing problem

Collaborative Mechanism for Pickup and Delivery Problems with Heterogeneous Vehicles under Time Windows

A review on the electric vehicle routing problems: Variants and algorithms

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