Dynamic vehicle routing problems: Three decades and counting

Psaraftis, Harilaos N.; Wen, Min; Kontovas, Christos A.

doi:10.1002/net.21628

Cited by 363 publications

(156 citation statements)

References 145 publications

(192 reference statements)

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“…That study classifies routing problems from the perspective of information quality (deterministic versus stochastic input) and evolution of information (whether or not the information available to the planner may change during the execution of the routes). Psaraftis et al (2016) also present a survey paper on Dynamic Vehicle Routing Problems and provide a taxonomy of DVRP papers according to 11 criteria: type of problem, logistical context, transportation mode, objective function, fleet size, time constraints, vehicle capacity constraints, the ability to reject customers, the nature of the dynamic element, the nature of the stochasticity (if any) and the solution method.…”

Section: : "At the Beginning Of A Business Cycle An Optimal Or Near-mentioning

confidence: 99%

Disruption management in vehicle routing and scheduling for road freight transport: a review

Eglese

Zambirinis

2018

TOP

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Disruption management is an approach to the rescheduling of operations following an unanticipated event occurring that has been applied in a wide range of applications, including airline scheduling and project management. This review focusses on the use of disruption management in vehicle routing and scheduling applied to road freight distribution. The paper discusses the key features of disruption management and examines the relevant objectives and types of disruption that may occur in this context. Different formulations and solution methods are described. A set of relevant papers are summarised and classified according to the type of disruption addressed, the relevant objectives and the solution approach.

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Section: : "At the Beginning Of A Business Cycle An Optimal Or Near-mentioning

confidence: 99%

Disruption management in vehicle routing and scheduling for road freight transport: a review

Eglese

Zambirinis

2018

TOP

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“…Due to recent advances in these technologies, they can now be implemented at lower costs and at a larger scale [21]. One can refer to [6,14,21] for complete reviews on the recent literature on the vehicle routing problems, and [23,24] for stochastic and dynamic vehicle routing problems.…”

Section: Literature Reviewmentioning

confidence: 99%

A look-ahead partial routing framework for the stochastic and dynamic vehicle routing problem

Zou

Dessouky

2018

J Veh Routing Algorithms

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In this paper, we study the vehicle routing problem with dynamic customers, where a portion of the customer requests are known in advance and the rest arrive in real time. We propose an optimization-based look-ahead dynamic routing framework that involves request forecasting, partial planning, and dynamic real-time routing of the fleet. This framework has the capabilities for adjustments in response to routing environments with different levels of uncertainties. Through extensive numeral simulations, we exam its performance in routing environments with various levels of uncertainties. We demonstrate the efficiency and robustness of the proposed solution by benchmarking against two other routing strategies. This paper fills the gap in the literature on studying the relationship between the level of route planning in the solution approach and the quality of the solution under various system conditions.

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“…Bekta et al [19] provided another survey in this area, which provided a deeper and more detailed analysis. Last but not least, Psaraftis et al [20] shed more light into work in this area, over more than 3 decades, by developing a taxonomy of DVRP papers according to 11 criteria.…”

Section: Related Workmentioning

confidence: 99%

A Monarch Butterfly Optimization for the Dynamic Vehicle Routing Problem

Chen

Gao

2017

Algorithms

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Abstract:The dynamic vehicle routing problem (DVRP) is a variant of the Vehicle Routing Problem (VRP) in which customers appear dynamically. The objective is to determine a set of routes that minimizes the total travel distance. In this paper, we propose a monarch butterfly optimization (MBO) algorithm to solve DVRPs, utilizing a greedy strategy. Both migration operation and the butterfly adjusting operator only accept the offspring of butterfly individuals that have better fitness than their parents. To improve performance, a later perturbation procedure is implemented, to maintain a balance between global diversification and local intensification. The computational results indicate that the proposed technique outperforms the existing approaches in the literature for average performance by at least 9.38%. In addition, 12 new best solutions were found. This shows that this proposed technique consistently produces high-quality solutions and outperforms other published heuristics for the DVRP.

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Dynamic vehicle routing problems: Three decades and counting

Cited by 363 publications

References 145 publications

Disruption management in vehicle routing and scheduling for road freight transport: a review

Disruption management in vehicle routing and scheduling for road freight transport: a review

A look-ahead partial routing framework for the stochastic and dynamic vehicle routing problem

A Monarch Butterfly Optimization for the Dynamic Vehicle Routing Problem

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