Separating capacity constraints in the CVRP using tabu search

Augerat, P.; Belenguer, José-Manuel; Benavent, Enrique; Corberán, Ángel; Naddef, Denis

doi:10.1016/s0377-2217(97)00290-7

Cited by 146 publications

(84 citation statements)

References 11 publications

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“…Para validar la metodología propuesta se consideran casos de prueba que pueden ser descargados en [24]. En la definición de la instancia n corresponde al número de clientes, k corresponde a la cantidad de vehículos disponibles y Q corresponde a la capacidad del vehículo.…”

Section: Resultsunclassified

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Solución del problema de ruteo capacitado considerando efectos ambientales mediante una técnica híbrida

2015

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En este artículo se propone el uso de una metodología híbrida para resolver el problema de ruteo de vehículos capacitado CVRP (Capacitated Vehicle Routing Problem) considerando efectos ambientales. El problema se resuelve bajo la estrategia de rutear primero y asignar después. La etapa de ruteo se resuelve de forma exacta mediante un modelo lineal entero. La etapa de asignación se realiza aplicando un algoritmo genético modificado que considera la secuencia encontrada en la etapa anterior como punto de partida para generar la población inicial. La función objetivo a optimizar corresponde a la minimización de distancia-peso recorrido a lo largo de la ruta, como indicador de impacto ambiental. La metodología se valida con casos de prueba de la literatura especializada

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Section: Resultsunclassified

“…Mutación: Se aplica una mutación especializada explicada en la referencia [24], sobre toda la población. Se denomina Dmutation.…”

Section: Cruzamientounclassified

Solución del problema de ruteo capacitado considerando efectos ambientales mediante una técnica híbrida

2015

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“…As the explicit enumeration is limited to small problem instances only (the complexity is at least n! ), a metaheuristic Ant Colony Optimization is introduced in the second section and applied on the benchmark problems described in Augerat et al [4] for both objective functions considered.…”

Section: Computational Resultsmentioning

confidence: 99%

“…This dataset is solved by explicit enumeration, i.e., all possible solutions are generated and evaluated both in distance and in travel times. The datasets are all random subsets of different problems from Augerat et al [4]. All coordinates are multiplied with a constant factor of five to ensure that multiple time zones are covered over longer distances.…”

Section: Explicit Enumerationmentioning

confidence: 99%

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A Queueing Framework for Routing Problems with Time-dependent Travel Times

Woensel¹,

Kerbache²,

Peremans³

et al. 2006

J Math Model Algor

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Assigning and scheduling vehicle routes in a dynamic environment is a crucial management problem. Despite numerous publications dealing with efficient scheduling methods for vehicle routing, very few addressed the inherent stochastic and dynamic nature of travel times. In this paper, a vehicle routing problem with time-dependent travel times due to potential traffic congestion is considered. The approach developed introduces the traffic congestion component based on queueing theory. This is an innovative modelling scheme to capture the stochastic behavior of travel times as it generates an analytical expression for the expected travel times as well as for the variance of the travel times. Routing solutions that perform well in the face of the extra complications due to congestion are developed. These more realistic solutions have the potential to reduce real operating costs for a broad range of industries which daily face routing problems. A number of datasets are used to illustrate the appropriateness of the novel approach. Moreover it is shown that static (or time-independent) solutions are often infeasible within a congested traffic environment which is generally the case on European road networks. Finally, the effect of travel time variability (obtained via the queueing approach) is quantified for the different datasets.

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Combining Exact Methods and Heuristics

Boschetti

Maniezzo

2011

Wiley Encyclopedia of Operations Research and Management Science

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The combination of exact and heuristic methods is as old as mathematical programming (MP) itself, because usually exact methods cannot work properly without a good bound on the optimal cost, which helps pruning the search space. However, it is only in very recent years that the combination has also gone the other way round, permitting the use of methods originally conceived for exact problem solution also in heuristic frameworks. In this article, we revise the newly identified field of metaheuristics, which refers in particular to algorithms combining metaheuristics with MP techniques and show how current research aims at exploiting MP and metaheuristics synergies.

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Separating capacity constraints in the CVRP using tabu search

Cited by 146 publications

References 11 publications

Solución del problema de ruteo capacitado considerando efectos ambientales mediante una técnica híbrida

Solución del problema de ruteo capacitado considerando efectos ambientales mediante una técnica híbrida

A Queueing Framework for Routing Problems with Time-dependent Travel Times

Combining Exact Methods and Heuristics

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