A branch-and-cut approach for the vehicle routing problem with loading constraints

Hokama, Pedro Henrique Del Bianco; Miyazawa, Flávio Keidi; Xavier, Eduardo C.

doi:10.1016/j.eswa.2015.10.013

Cited by 46 publications

(20 citation statements)

References 25 publications

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“…The authors Iori et al (2007) solved the underlying problem to optimality with a branch-and-cut method for instances involving up to 30 customers and 90 boxes. Lately, Côté et al (2014) and Hokama et al (2016) presented improved branch-and-cut methods for the first 60 instances of the 180 created 2L-CVRP instances reported in Gendreau et al (2007). Most of the 2L-CVRP instances were tackled with heuristic, meta-heuristic and evolutionary methods.…”

Section: Literature Reviewmentioning

confidence: 99%

Multi-objective vehicle routing and loading with time window constraints: a real-life application

et al. 2019

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Motivated by a real-life application, this research considers the multi-objective vehicle routing and loading problem with time window constraints which is a variant of the Capacitated Vehicle Routing Problem with Time Windows with one/two-dimensional loading constraints. The problem consists of routing a number of vehicles to serve a set of customers and determining the best way of loading the goods ordered by the customers onto the vehicles used for transportation. The three objectives pertaining to minimisation of total travel distance, number of routes to use and total number of mixed orders in the same pallet are, more often than not, conflicting. To achieve a solution with no preferential information known in advance from the decision maker, the problem is formulated as a Mixed Integer Linear Programming (MILP) model with one objective-minimising the total cost, where the three original objectives are incorporated as parts of the total cost function. A Generalised Variable Neighbourhood Search (GVNS) algorithm is designed as the search engine to relieve the computational burden inherent to the application of the MILP model. To evaluate the effectiveness of the GVNS algorithm, a real instance case study is generated and solved by both the GVNS algorithm and the software provided by our industrial partner. The results show that the suggested approach provides solutions with better overall values than those found by the software provided by our industrial partner.

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Section: Literature Reviewmentioning

confidence: 99%

Multi-objective vehicle routing and loading with time window constraints: a real-life application

et al. 2019

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“…As practical loading constraints, the authors have included LIFO loading/unloading and the rotation of items, which according to the authors is not a commonly considered condition in 2D versions of the problem. Hokama et al (2016) presented optimization models for solving 2D and 3D VRPLC, with the objective of minimizing costs. Apart from the classic packing and routing constraints, LIFO loading/unloading is taken into consideration.…”

Section: Previous Studiesmentioning

confidence: 99%

A nonlinear optimization model for the balanced vehicle routing problem with loading constraints

Vega-Mejía

Montoya‐Torres

Islam

2018

Int Trans Operational Res

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The vehicle routing problem with loading constraints (VRPLC) is related to real‐life transportation problems and integrates two of the most important activities in distribution logistics: packing of items inside vehicles and planning of delivery routes. In spite of its relevance, literature on VRPLCs is still limited. The majority of the solution approaches have concentrated on heuristic solution methods, and few have presented mathematical optimization models to help characterize the problem. Furthermore, few studies have considered several practical loading and routing constraints that could be used to approximate the problem toward more realistic situations. To help fill this gap in the literature, this article extends an existing VRPLC optimization model to a nonlinear optimization model that considers weight‐bearing strength of three‐dimensional items, vehicle weight capacity, weight distribution inside vehicles, delivery time windows, and a balanced fleet of vehicles. The model is solved by applying a simple procedure that isolates the nonlinearity of the model. Computational experiments show that the new proposed model gives a more streamlined formulation than the model it extended on, and that the addition of practical loading constraints can improve the solutions of the original model by reducing the measure of tardiness due to late deliveries and by producing cargo patterns with better weight distribution.

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“…In recent years, there has been growing interest in the simultaneous determination of both the optimal routes and the packing patterns of vehicles, as this combination can assist in producing better global solutions for distribution logistics (Hokama et al, 2016). This can be carried out by modeling and solving a problem known as the Vehicle Routing Problem with Loading Constraints (VRPLC) (Zachariadis, Tarantilis, & Kiranoudis, 2013).…”

Section: Introductionmentioning

confidence: 99%

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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A branch-and-cut approach for the vehicle routing problem with loading constraints

Cited by 46 publications

References 25 publications

Multi-objective vehicle routing and loading with time window constraints: a real-life application

Multi-objective vehicle routing and loading with time window constraints: a real-life application

A nonlinear optimization model for the balanced vehicle routing problem with loading constraints

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

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