Chapter 5: The Vehicle Routing Problem with Time Windows

Desaulniers, Guy; Madsen, Oli B.G.; Røpke, Stefan

doi:10.1137/1.9781611973594.ch5

Cited by 97 publications

(79 citation statements)

References 73 publications

(120 reference statements)

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“…The bPRP considers the same constraints found in the VRPTW, where in addition to the constraints defined for the classical VRP, it also imposes that each customer

i \in V'

can only start to be served within its time window

[a_{i}, b_{i}]

. The bPRP has two objective functions, which are treated separately: the first aims at minimizing the costs from CO 2 emissions while the second aims at minimizing the total costs associated with drive wages.…”

Section: Problem Descriptionmentioning

confidence: 99%

A two‐phase Pareto local search heuristic for the bi‐objective pollution‐routing problem

et al. 2018

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This article deals with the bi‐objective pollution‐routing problem (bPRP), a vehicle routing variant that arises in the context of green logistics. The two conflicting objectives considered are the minimization of the CO2 emissions and the costs related to driver's wages. A multi‐objective approach based on the two‐phase Pareto local search heuristic is employed to generate a good approximation of the Pareto front. During the first phase of the method, a first set of potentially efficient solutions is obtained by solving a series of weighted sum problems with an efficient heuristic originally developed to solve the single‐objective PRP. A dichotomous scheme is used to generate the different weight sets in an automatic way. In the second phase, the set is improved with an efficient Pareto local search (PLS) procedure. The use of PLS allows to limit the number of computational demanding weighted sum problems solved in the first phase, while keeping high‐quality results. Extensive computational experiments over existing benchmark instances show that the proposed approach leads to better results in less CPU time when compared to those obtained by state‐of‐the‐art methods.

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“…The bPRP considers the same constraints found in the VRPTW, where in addition to the constraints defined for the classical VRP, it also imposes that each customer

i \in V'

can only start to be served within its time window

[a_{i}, b_{i}]

Section: Problem Descriptionmentioning

confidence: 99%

A two‐phase Pareto local search heuristic for the bi‐objective pollution‐routing problem

et al. 2018

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“…The problem is also referred to in the literature as the Pickup and Delivery Problem with Time Window (PDPTW). The problem can be also considered as a version of the general Vehicle Routing Problem with Time Window (VRPTW), which is extensively studied in the literature (Psaraftis, ; Cordeau et al., ; Desaulniers et al., ). As these problems are proved to be NP‐hard, existing solution methodologies adopt heuristic‐based approaches that solve for near‐optimal solutions.…”

Section: Literature Reviewmentioning

confidence: 99%

Modeling Framework and Decomposition Scheme for On‐Demand Mobility Services with Ridesharing and Transfer

Lotfi

Abdelghany

Hashemi

2018

Computer aided Civil Eng

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This article presents a modeling framework for the operations of on‐demand mobility services (ODMS) in urban areas. The framework provides the capabilities to analyze ODMS operations while representing emerging services such as ridesharing and transfer. The problem is formulated as a mixed integer program and an efficient decomposition‐based methodology is developed for its solution. The methodology adopts a modified version of the column generation algorithm, which implements iterative decomposition and network augmentation techniques to allow studying networks of moderate size. The results of a set of experiments considering grid and real‐world networks are presented. The results show that increasing the number of passengers willing to rideshare and/or transfer improves the overall performance of ODMS as it increases number of served passengers and associated profit and reduces the number of used vehicles. Although presented as an offline planning tool, the methodology could be adopted for real‐time applications as adequate computational resources become available.

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“…The problem of vehicle routing with time windows (VRPTW) is one of the most widely studied and researched VRP variants with published papers, including ([4]- [7]) provides a comprehensive overview of the precise and heuristic methods for VRPTW. ( [5]) provide an overview and advanced heuristic analysis to solve large-scale VRPTW.…”

Section: Related Workmentioning

confidence: 99%

The Open Vehicle Routing Problem With Time Windows Considering Driver’s Working Hour

Amir¹

2018

IJRASET

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This paper presents an optimization model for a logistic management called open vehicle routing problem with time windows with driver's working time (OVRPTWWDWT). This is an extension of the classical OVRPTW which considers driver's working time to model the scheduling of the available drivers with respect of the driving time to satisfy customers' demand. The objective is to schedule the delivery according to the driver's working time and to determine the fleet scheduling and the driver's policy in serving the customer, such that to minimize the amount of cost over all the routes within the planning horizon. We propose a tabu search heuristic algorithms approach to solve the problem.

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Chapter 5: The Vehicle Routing Problem with Time Windows

Cited by 97 publications

References 73 publications

A two‐phase Pareto local search heuristic for the bi‐objective pollution‐routing problem

A two‐phase Pareto local search heuristic for the bi‐objective pollution‐routing problem

Modeling Framework and Decomposition Scheme for On‐Demand Mobility Services with Ridesharing and Transfer

The Open Vehicle Routing Problem With Time Windows Considering Driver’s Working Hour

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