Heuristic algorithms for a three-dimensional loading capacitated vehicle routing problem in a carrier

Junqueira, Leonardo; Morábito, Reinaldo

doi:10.1016/j.cie.2015.06.005

Cited by 35 publications

(13 citation statements)

References 40 publications

(48 reference statements)

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“…Tricoire et al, 2011). According to Junqueira and Morabito (2015), these solution approaches can be grouped into three distinctive approaches. The first one is called "loading after routing", which basically determines the delivery routes of the vehicles first, and then starts validating that the loading patterns are feasible.…”

Section: Introductionmentioning

confidence: 99%

“…According to their classification, the VRPLC is a type of RVRP. Regarding VRPLCs, the recent reviews by Iori and Martello (2010) and Junqueira and Morabito (2015) presented an account of the algorithmic approaches used to solve the problem. To the best of our knowledge, the most recent review on VRPLCs corresponds to the work by Vega-Mejía, Montoya-Torres and Islam (2019b), who analyzed how the different attributes of the problem (i.e.…”

Section: Introductionmentioning

confidence: 99%

“…However, Bortfeldt and Wäscher (2013) concluded from their review work on Packing Problems (PP), that many of the practical constraints originally described by Bischoff and Ratcliff (1995) had been neglected in PP studies. Moreover, Iori and Martello (2010) and Junqueira and Morabito (2015) suggested the inclusion of several operational attributes of the VRPLC (e.g. split deliveries, weight distribution, route balancing, time windows, pickup and delivery) as future research directions in the development of solution methods.…”

Section: Introductionmentioning

confidence: 99%

“…split deliveries, weight distribution, route balancing, time windows, pickup and delivery) as future research directions in the development of solution methods. In their review, Junqueira and Morabito (2015) showed that studies have mostly concentrated on ten practical constraints: (i) Rotation of items, (ii) vertical stability, (iii) Last In -First Out (LIFO) loading/unloading, (iv) fragility of items, (v) box to pallets and pallets into vehicles, (vi) weight related constraints, (vii) time windows, (viii) timeconstrained routes, (ix) pickup and delivery, (x) and split deliveries. However, the studies they analyzed considered only half of these attributes, at the most.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Using a hybrid heuristic to solve the balanced vehicle routing problem with loading constraints

Vega-Mejía¹,

González-Neira²,

Montoya‐Torres³

et al. 2020

10.5267/j.ijiec

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The Vehicle Routing Problem with Loading Constraints (VRPLC) is strongly related to real life applications in distribution logistics. It addresses the simultaneous loading and routing of vehicles, which are two crucial activities in transportation. Since treating these operations separately may result in impractical solutions, the development of applications for VRPLCs has gained the attention of researchers in recent years. Several heuristic methods have been proposed, but they consider only a limited group of practical characteristics that arise in real world situations. This study proposes a hybrid heuristic method based on the Greedy Randomized Adaptive Search Procedure (GRASP) metaheuristic and the Clarke and Wright Savings algorithm, to solve a VRPLC with several loading and routing constraints that have not been considered simultaneously before. Experimental results show that the proposed procedure produces competitive solutions in short processing times. Lastly, the impact of the added operational constraints is also analyzed.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Using a hybrid heuristic to solve the balanced vehicle routing problem with loading constraints

Vega-Mejía¹,

González-Neira²,

Montoya‐Torres³

et al. 2020

10.5267/j.ijiec

View full text Add to dashboard Cite

show abstract

“…Included among the most significant extensions are the following: the Multi-Depot Capacitated Arc Routing Problem with Full Truckloads (Liu et al 2010); the Multi-Depot Split Delivery VRP (Ray et al 2014); the CVRP model with fuel consumption optimisation (Xiao et al 2012); the VRP with Time Windows (Jabali et al 2015;Savelsbergh 1985); and the three-dimensional loading Capacitated VRP (Junqueira & Morabito 2015). Also, because of its computational non-deterministic polynomial-time hardness (NP-hard complexity), diverse algorithms have been developed to solve the CVRP to near-optimality.…”

Section: Literature Reviewmentioning

confidence: 99%

Capacitated vehicle routing problem model for carriers

Rojas-Cuevas

Caballero‐Morales

Martínez‐Flores

et al. 2018

J. transp. supply chain manag.

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Background: The Capacitated Vehicle Routing Problem (CVRP) is one of the most important transportation problems in logistics and supply chain management. The standard CVRP considers a fleet of vehicles with homogeneous capacity that depart from a warehouse, collect products from (or deliver products to) a set of customer locations (points) and return to the same warehouse. However, the operation of carrier companies and third-party transportation providers may follow a different network flow for collection and delivery. This may lead to non-optimal route planning through the use of the standard CVRP.Objective: To propose a model for carrier companies to obtain optimal route planning.Method: A Capacitated Vehicle Routing Problem for Carriers (CVRPfC) model is used to consider the distribution scenario where a fleet of vehicles depart from a vehicle storage depot, collect products from a set of customer points and deliver them to a specific warehouse before returning to the vehicle storage depot. Validation of the model’s functionality was performed with adapted CVRP test problems from the Vehicle Routing Problem LIBrary. Following this, an assessment of the model’s economic impact was performed and validated with data from a real carrier (real instance) with the previously described distribution scenario.Results: The route planning obtained through the CVRPfC model accurately described the network flow of the real instance and significantly reduced its distribution costs.Conclusion: The CVRPfC model can thus improve the competitiveness of the carriers by providing better fares to their customers, reducing their distribution costs in the process.

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Automatic Generator of Loading Rules and Its Applications on Logistics Operations

Azevedo

2021

Lecture Notes in Networks and Systems

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Heuristic algorithms for a three-dimensional loading capacitated vehicle routing problem in a carrier

Cited by 35 publications

References 40 publications

Using a hybrid heuristic to solve the balanced vehicle routing problem with loading constraints

Using a hybrid heuristic to solve the balanced vehicle routing problem with loading constraints

Capacitated vehicle routing problem model for carriers

Automatic Generator of Loading Rules and Its Applications on Logistics Operations

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