Vehicle Routing Problem with Time Windows, Part I: Route Construction and Local Search Algorithms

By Olli Bräysy, Michel Gendreau. Transportation Science, 2005

1,259 citations recorded by the source corpus.

Subfields: Automotive Engineering, Computer Vision and Pattern Recognition, Industrial and Manufacturing Engineering

View Paper: https://www.semanticscholar.org/paper/52fd225a60400f66e6d8da96d27a73dff8146e89

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In Automotive Engineering

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In Industrial and Manufacturing Engineering

Citations in the corpus

Improved route planning and scheduling of waste collection and transport (2006, methodology): “For more information on VRPTW, we refer to recent extensive two-part survey paper by Bräysy and Gendreau (2005a,b). In the literature, the size of the vehicle fleet is often part of the optimization problem. However, in practice, a transportation company usually has a given fixed number of vehicles,”
Rich vehicle routing problems: From a taxonomy to a definition (2015, background): “Bräysy and Gendreau (2005a, 2005b), Kallehauge, Larsen, Madsen, and Solomon (2005), Kallehauge (2008), and Gendreau and Tarantilis (2010) propose recent surveys on this problem.”
Quality, safety and sustainability in food distribution: a review of quantitative operations management approaches and challenges (2010, methodology): “For a detailed discussion of solution methods, we refer to Bräysy and Gendreau (2005b) or Tarantilis et al. (2005).”
A hybrid genetic algorithm with adaptive diversity management for a large class of vehicle routing problems with time-windows (2013, methodology): “As illustrated by numerous reviews (Bräysy and Gendreau 2005b,a, Francis et al. 2008, Gendreau et al. 2008, Gendreau and Tarantilis 2010, for the most recent), almost every prominent meta-heuristic paradigm, including evolutionary methods, ant colony optimization, tabu search, simulated annealing ,…”
Vehicle Routing Problem with Time Windows, Part II: Metaheuristics (2005, background): “Chiang and Russell (1997), Schulze and Fahle (1999), and Cordeau et al. (2001) use a similar strategy for diversification, but in Chiang and Russell (1997) the intensification is used to reduce waiting time by forbidding certain customers from moving into another route.”
The time-dependent vehicle routing problem with soft time windows and stochastic travel times (2014, neutral): “The interested reader is referred to Br¨aysy and Gendreau (2005a,b) for reviews on the VRPTW.”
Multi-Objective Genetic Algorithms for Vehicle Routing Problem with Time Windows (2006, background): “As a result, variants of VRP have been studied extensively in the literature (for detailed reviews, see [ 1-4 ]).”
E-fulfillment and multi-channel distribution - A review (2006, background): “Braysy and Gendreau (2005a,b) provide a recent survey of solution algorithms for vehicle routing problems with time windows (VRPTW).”
The Electric Vehicle-Routing Problem with Time Windows and Recharging Stations (2014, background): “In the VRPTW, service at a customer has to start within a given time interval, which is a highly relevant constraint in real-world routing applications (see, e.g., Bräysy and Gendreau 2005a).”
The Electric Fleet Size and Mix Vehicle Routing Problem with Time Windows and Recharging Stations (2016, positive): “A survey on this problem class is provided in Br¨aysy and Gendreau (2005a,b); Toth and Vigo (2014).”
A survey of variants and extensions of the location-routing problem (2015, methodology): “(see Cordeau et al. 2002, Bräysy and Gendreau 2005).”
A Tutorial On the design, experimentation and application of metaheuristic algorithms to real-World optimization problems (2021, background): “…intelligence algorithms [9] Resource-constrained project scheduling problems [10] — [11] Multi-objective problems [12] — [28] Swarm Intelligence [29] Vehicle Routing Problems with Time Windows [30] Vehicle Routing Problems [31] Common pitfalls and good practices for parameter tuning [32] — [33]…”
Heavy-Duty Vehicle Platooning for Sustainable Freight Transportation: A Cooperative Method to Enhance Safety and Efficiency (2015, background): “This vehicle routing problem has high computational complexity (specifically, it is NP-hard), but several heuristic approaches exist [20].”