A Multi-Objective Genetic Algorithm for the Vehicle Routing with Time Windows and Loading Problem

Moura, Ana

doi:10.1007/978-3-8349-9777-7_11

Cited by 38 publications

(21 citation statements)

References 19 publications

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“…This constraint is commonly used in VRPs (e.g. Iori et al 2007;Gendreau et al 2006;Moura 2008;Doerner et al 2007) and is sometimes referred to as a last-in-first-out (LIFO) constraint. It is important to note, though, that only when a single dimension is considered, it is truly LIFO that is applied, since in a two-and three-dimensional problem items can be placed beside each other.…”

Section: Positioning Constraintsmentioning

confidence: 99%

“…Sequence-based loading is incorporated in most models as shown in Table 1. Most papers assume a homogeneous fleet, while only three papers consider time windows (Moura 2008;Moura and Oliveira 2009;Bortfeldt and Homberger 2013). An exact solution method and a formulation of the 3L-CVRP is provided by Junqueira et al (2013).…”

Section: Three-dimensional Loading Cvrpmentioning

confidence: 99%

“…The routes are planned first, and afterwards, for each route, the items are packed into the vehicles. As in Moura (2008), the model considers sequence-based loading, orientation constraints and stability constraints. In the sequential approach, the container loading and the vehicle routes are planned at the same time.…”

Section: Three-dimensional Loading Cvrpmentioning

confidence: 99%

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Vehicle routing problems with loading constraints: state-of-the-art and future directions

et al. 2014

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Distributors are faced with loading constraints in their route planning, e.g.,multi-dimensional packing constraints, unloading sequence constraints, stability constraints and axle weight limits. Ignoring these constraints impairs planning and induces last-minute changes resulting in additional costs. Developing vehicle routing models incorporating loading constraints is critical to more efficient route planning. The last couple of years has seen a huge increase of contributions to this field of research with almost 60 % of these being published after 2009. Our contribution is twofold. First, we overview the recent developments in the literature on all vehicle types in which loading constraints play a key role (trucks, airplanes, ships, and automated guided vehicles), using a state-of-the-art classification scheme to identify the loading constraints considered in each article. Second, we identify research gaps and opportunities for future research.

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Section: Positioning Constraintsmentioning

confidence: 99%

Section: Three-dimensional Loading Cvrpmentioning

confidence: 99%

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Vehicle routing problems with loading constraints: state-of-the-art and future directions

et al. 2014

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“…Moura and Oliveira (2009) addressed the issue of integrating the CVRP with time windows and three-dimensional container loading, proposing a number of constructive heuristics. Moura (2008) modeled the same problem as a multi-objective problem in which the multi-objective function space has three dimensions (number of vehicles, total traveled distance and volume utilization), and presented a genetic algorithm for its solution.…”

Section: Vehicle Routing Problems With Multi-compartment Loadingmentioning

confidence: 99%

Routing problems with loading constraints

Iori

Martello

2010

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190

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We consider difficult combinatorial optimization problems arising in transportation logistics when one is interested in optimizing both the routing of vehicles and the loading of goods into them. The separate problems (routing and loading) are already NP-hard, and very difficult to solve in practice. A fortiori their combination is extremely challenging and stimulating. Although the specific literature is still quite limited, a first attempt to a systematic view of this field can be useful both to academic researchers and to practitioners. We review vehicle routing problems with twoand three-dimensional loading constraints. Other combinations of routing and special loading constraints arising from industrial applications are also considered

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“…In this work, several constructive heuristics are addressed. In [14], an extension of the previous described work [13] is presented. In particular, a multi objective scheme is proposed by considering the following objective functions: minimizing the number of vehicles, minimizing the total travel distance, and maximizing the used volume.…”

Section: Problem Definitionmentioning

confidence: 99%

A matheuristic algorithm for the three-dimensional loading capacitated vehicle routing problem (3L-CVRP)

Escobar-Falcón

Álvarez‐Martínez

Echeverri

et al. 2015

Rev. Fac. Ing. Antioquia

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This paper presents a hybrid algorithm for solving the Capacitated VehicleRouting Problem with practical three-dimensional loading constraint. This problem is known as 3L-CVRP (Three-dimensional Loading Capacitated Vehicle Routing Problem). The proposed methodology consists of two phases. The first phase uses an optimization procedure based on cuts to obtain solutions for the well-known Capacitated Vehicle Routing Problem (CVRP). The second phase validates the results of the first phase of a GRASP algorithm (Greedy Randomized Adaptive Search Procedure). In particular, the GRASP approach evaluates the packing constraints for each performed route of the CVRP. The proposed hybrid algorithm uses a relaxation of the classical model of two sub-indices for the vehicle routing problem. Specifically different types of cuts are added: subtour elimination, capacity-cut constraints, and packing-cut constrains. The proposed algorithm is compared with the most efficient approaches for the 3L-CVRP on the set of benchmark instances considered in the literature. The computational results indicate that the proposed approach is able to obtain good solutions, improving some of the best-known solutions from the literature. RESUMEN:En este artículo se presenta un algoritmo híbrido para resolver el problema de ruteo de vehículos con restricciones de capacidad y restricciones prácticas de empaquetamiento tridimensional, este problema en la literatura es conocido como 3L-CVRP (Capacitated Vehicle Routing Problem and Container Loading Problem). La metodología de solución propuesta en este trabajo consiste de dos fases. La primera utiliza un procedimiento de optimización basado en cortes para el Problema de Rutas de Vehículos Capacitados (CVRP). La segunda valida las soluciones de la fase anterior a través de un algoritmo GRASP (Greedy Randomized Adaptive Search Procedure), el cual evalúa las restricciones de empaquetamiento de cada una de las rutas. Para el algoritmo híbrido se utiliza la relajación del modelo clásico de dos subíndices para el problema de ruteo de vehículos. En particular diferentes tipos de cortes son adicionados: eliminación de subtours, cortes debido a las restricciones de capacidad y cortes para restricciones de empaquetamiento. El algoritmo propuesto ha sido comparado con los algoritmos más eficaces para el 3L-CVRP en el conjunto clásico de instancias presentadas en la literatura. Los resultados computacionales muestran que el método propuesto es capaz de obtener buenos resultados perfeccionando algunas de las mejores soluciones conocidas propuestas en la literatura.

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A Multi-Objective Genetic Algorithm for the Vehicle Routing with Time Windows and Loading Problem

Cited by 38 publications

References 19 publications

Vehicle routing problems with loading constraints: state-of-the-art and future directions

Vehicle routing problems with loading constraints: state-of-the-art and future directions

Routing problems with loading constraints

A matheuristic algorithm for the three-dimensional loading capacitated vehicle routing problem (3L-CVRP)

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