A literature review on the vehicle routing problem with multiple depots

Montoya‐Torres, Jairo R.; Franco, Julián López; Isaza, Santiago Nieto; Jiménez, Heriberto Felizzola; Herazo-Padilla, Nilson

doi:10.1016/j.cie.2014.10.029

Cited by 365 publications

(182 citation statements)

References 126 publications

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“…Prins et al [39] presented a memetic algorithm with population management (MAPM). The main idea behind MAPM is that LS is used to improve the solution generated by GA. A similar method was described by Derbel et al [40]; iterative local search [41] is adopted to improve the solution generated by the GA. Marinakis and Marinaki [42] formulated a bi-level programming for LRP, and a bi-level GA was designed to solve the problem accordingly. In this method, GA is used to locate the facilities in the first level and the VRP in the second level is solved by expanding neighborhood search (ENS).…”

Section: Introductionmentioning

confidence: 99%

Location-Routing Problem with Simultaneous Home Delivery and Customer’s Pickup for City Distribution of Online Shopping Purchases

Zhou

Wang

et al. 2016

Sustainability

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Abstract:With the increasing interest in online shopping, the Last Mile delivery is regarded as one of the most expensive and pollutive-and yet the least efficient-stages of the e-commerce supply chain. To address this challenge, a novel location-routing problem with simultaneous home delivery and customer's pickup is proposed. This problem aims to build a more effective Last Mile distribution system by providing two kinds of service options when delivering packages to customers. To solve this specific problem, a hybrid evolution search algorithm by combining genetic algorithm (GA) and local search (LS) is presented. In this approach, a diverse population generation algorithm along with a two-phase solution initialization heuristic is first proposed to give high quality initial population. Then, advantaged solution representation, individual evaluation, crossover and mutation operations are designed to enhance the evolution and search efficiency. Computational experiments based on a large family of instances are conducted, and the results obtained indicate the validity of the proposed model and method.

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Section: Introductionmentioning

confidence: 99%

Location-Routing Problem with Simultaneous Home Delivery and Customer’s Pickup for City Distribution of Online Shopping Purchases

Zhou

Wang

et al. 2016

Sustainability

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“…Montoya-Torres et al [6] illustrate the hierarchy of the VRP variants with Figure 2. According to them, the most impressive growing of VRP study was observed between 2006 and 2014 with a total of 103 publications.…”

Section: Researches On Vrpmentioning

confidence: 99%

Multiple Depots Vehicle Routing Problem in the Context of Total Urban Traffic Equilibrium

Chen

Yang

2017

Journal of Advanced Transportation

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A multidepot VRP is solved in the context of total urban traffic equilibrium. Under the total traffic equilibrium, the multidepot VRP is changed to GDAP (the problem of Grouping Customers + Estimating OD Traffic + Assigning traffic) and bilevel programming is used to model the problem, where the upper model determines the customers that each truck visits and adds the trucks' trips to the initial OD (Origin/Destination) trips, and the lower model assigns the OD trips to road network. Feedback between upper model and lower model is iterated through OD trips; thus total traffic equilibrium can be simulated.

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“…In the recent years, it has attracted more and more attention and studied widely. For the first time, the VRP was proposed by Dantzig and Ramser (1959) and then has been studied widely (e.g., Montoya-Torres et al, 2015;Pillac et al, 2013). In the VRPTW, the time window concept is considered due to a customer may need the earliest and latest service times.…”

Section: Introductionmentioning

confidence: 99%

Solving a bi-objective vehicle routing problem under uncertainty by a revised multi-choice goal programming approach

Yousefi¹,

Tavakkoli–Moghaddam²,

Oliaei³

et al. 2017

10.5267/j.ijiec

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A vehicle routing problem with time windows (VRPTW) is an important problem with many real applications in a transportation problem. The optimum set of routes with the minimum distance and vehicles used is determined to deliver goods from a central depot, using a vehicle with capacity constraint. In the real cases, there are other objective functions that should be considered. This paper considers not only the minimum distance and the number of vehicles used as the objective function, the customer's satisfaction with the priority of customers is also considered. Additionally, it presents a new model for a bi-objective VRPTW solved by a revised multi-choice goal programming approach, in which the decision maker determines optimistic aspiration levels for each objective function. Two meta-heuristic methods, namely simulated annealing (SA) and genetic algorithm (GA), are proposed to solve large-sized problems. Moreover, the experimental design is used to tune the parameters of the proposed algorithms. The presented model is verified by a real-world case study and a number of test problems. The computational results verify the efficiency of the proposed SA and GA.

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A literature review on the vehicle routing problem with multiple depots

Cited by 365 publications

References 126 publications

Location-Routing Problem with Simultaneous Home Delivery and Customer’s Pickup for City Distribution of Online Shopping Purchases

Location-Routing Problem with Simultaneous Home Delivery and Customer’s Pickup for City Distribution of Online Shopping Purchases

Multiple Depots Vehicle Routing Problem in the Context of Total Urban Traffic Equilibrium

Solving a bi-objective vehicle routing problem under uncertainty by a revised multi-choice goal programming approach

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