Recent Developments in Real Life Vehicle Routing Problem Applications

Simeonova, Lina; Wassan, Niaz A.; Wassan, Naveed; Salhi, Saïd

doi:10.1007/978-3-030-45312-1_8

Cited by 4 publications

(2 citation statements)

References 64 publications

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“…Apart from this basic version, multiple extensions of the problem can be found in the literature, to name a few: heterogeneous fleet of vehicles [11,12], time-windows [13,14], multiple depots [15,16], multiple delivery levels [17,18] simultaneous pick-up and deliveries [19,20], or combination of the former [21][22][23]. Many real-life versions of this problem combine some of the aforementioned constraints and others, making them difficult to solve [24].…”

Section: The Vehicle Routing Problemmentioning

confidence: 99%

Fuzzy Simheuristics for Optimizing Transportation Systems: Dealing with Stochastic and Fuzzy Uncertainty

et al. 2021

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In the context of logistics and transportation, this paper discusses how simheuristics can be extended by adding a fuzzy layer that allows us to deal with complex optimization problems with both stochastic and fuzzy uncertainty. This hybrid approach combines simulation, metaheuristics, and fuzzy logic to generate near-optimal solutions to large scale NP-hard problems that typically arise in many transportation activities, including the vehicle routing problem, the arc routing problem, or the team orienteering problem. The methodology allows us to model different components–such as travel times, service times, or customers’ demands–as deterministic, stochastic, or fuzzy. A series of computational experiments contribute to validate our hybrid approach, which can also be extended to other optimization problems in areas such as manufacturing and production, smart cities, telecommunication networks, etc.

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Section: The Vehicle Routing Problemmentioning

confidence: 99%

Fuzzy Simheuristics for Optimizing Transportation Systems: Dealing with Stochastic and Fuzzy Uncertainty

et al. 2021

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“…Depending on the specific characteristics of the transportation activity, different families of problems can be found in the scientific literature. Among the most popular ones, we can include vehicle routing problems (VRPs) [11][12][13], arc routing problems (ARPs) [14,15], and team orienteering problems (TOPs) [16,17]. These problems, which can model scenarios involving both road and aerial EVs, are NP-hard even in their simplest versions.…”

Section: Introductionmentioning

confidence: 99%

Electric Vehicle Routing, Arc Routing, and Team Orienteering Problems in Sustainable Transportation

et al. 2021

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The increasing use of electric vehicles in road and air transportation, especially in last-mile delivery and city mobility, raises new operational challenges due to the limited capacity of electric batteries. These limitations impose additional driving range constraints when optimizing the distribution and mobility plans. During the last years, several researchers from the Computer Science, Artificial Intelligence, and Operations Research communities have been developing optimization, simulation, and machine learning approaches that aim at generating efficient and sustainable routing plans for hybrid fleets, including both electric and internal combustion engine vehicles. After contextualizing the relevance of electric vehicles in promoting sustainable transportation practices, this paper reviews the existing work in the field of electric vehicle routing problems. In particular, we focus on articles related to the well-known vehicle routing, arc routing, and team orienteering problems. The review is followed by numerical examples that illustrate the gains that can be obtained by employing optimization methods in the aforementioned field. Finally, several research opportunities are highlighted.

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