Dynamic vehicle routing problems: Three decades and counting

Networks, Journal Year: 2015, Volume and Issue: 67(1), P. 3 - 31

Published: Aug. 17, 2015

Since the late 70s, much research activity has taken place on class of dynamic vehicle routing problems (DVRP), with time period after year 2000 witnessing a real explosion in related papers. Our paper sheds more light into work this area over than 3 decades by developing taxonomy DVRP papers according to 11 criteria. These are (1) type problem, (2) logistical context, (3) transportation mode, (4) objective function, (5) fleet size, (6) constraints, (7) capacity (8) ability reject customers, (9) nature element, (10) stochasticity (if any), and (11) solution method. We comment technological vis‐à‐vis methodological advances for suggest directions further research. The latter include alternative functions, speed as decision variable, explicit linkages methodology analysis worst case or average performance heuristics. © 2015 Wiley Periodicals, Inc. NETWORKS, Vol. 67(1), 3–31 2016

Language: Английский

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Ant Colony Optimization: Overview and Recent Advances

International series in management science/operations research/International series in operations research & management science, Journal Year: 2018, Volume and Issue: unknown, P. 311 - 351

Published: Sept. 20, 2018

Language: Английский

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A survey of swarm intelligence for dynamic optimization: Algorithms and applications

Swarm and Evolutionary Computation, Journal Year: 2017, Volume and Issue: 33, P. 1 - 17

Published: Jan. 11, 2017

Language: Английский

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A path planning approach for crowd evacuation in buildings based on improved artificial bee colony algorithm

Applied Soft Computing, Journal Year: 2018, Volume and Issue: 68, P. 360 - 376

Published: April 13, 2018

Language: Английский

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Vehicle routing problem and related algorithms for logistics distribution: a literature review and classification

Operational Research, Journal Year: 2020, Volume and Issue: 22(3), P. 2033 - 2062

Published: Sept. 9, 2020

Language: Английский

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Optimization and Machine Learning Applied to Last-Mile Logistics: A Review

Sustainability, Journal Year: 2022, Volume and Issue: 14(9), P. 5329 - 5329

Published: April 28, 2022

The growth in e-commerce that our society has faced recent years is changing the view companies have on last-mile logistics, due to its increasing impact whole supply chain. New technologies are raising users’ expectations with need develop customized delivery experiences; moreover, pressure chains also created additional challenges for suppliers. At same time, this phenomenon generates an increase liveability of cities, traffic congestion, occupation public spaces, and environmental acoustic pollution linked urban logistics. In context, optimization deliveries imperative not only parcels be delivered areas, but administrations want guarantee a good quality life citizens. years, many scholars focused study logistics techniques and, particular, last mile. addition traditional techniques, disciplines operations research, advances use sensors IoT, consequent large amount data derives from it, pushing towards greater big analytics techniques—such as machine learning artificial intelligence—which sector. Based premise, aim work provide overview most literature related techniques; used baseline who intend explore new approaches optimization. A bibliometric analysis critical review were conducted order highlight main studied problems, algorithms used, case studies. results allow studies clustered into models, approaches, mixed methods. research gaps limitations current assessed identify unaddressed suggestions future approaches.

Language: Английский

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Multi-depot vehicle routing problem for hazardous materials transportation: A fuzzy bilevel programming

Information Sciences, Journal Year: 2017, Volume and Issue: 399, P. 201 - 218

Published: Feb. 6, 2017

Language: Английский

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A multiple colonies artificial bee colony algorithm for a capacitated vehicle routing problem and re-routing strategies under time-dependent traffic congestion

Computers & Industrial Engineering, Journal Year: 2017, Volume and Issue: 109, P. 151 - 168

Published: May 3, 2017

Language: Английский

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On modeling stochastic dynamic vehicle routing problems

EURO Journal on Transportation and Logistics, Journal Year: 2020, Volume and Issue: 9(2), P. 100008 - 100008

Published: June 1, 2020

Operations research requires models that unambiguously define problems and support the generation presentation of solution methodology. In field dynamic routing, capturing joint evolution complex sequential routing decisions stochastic information is challenging, leading to a situation where rigorous methods have outpaced thus making it difficult for researchers engage in science. We provide modeling framework strongly connects application with method leverages rich body route-based planning optimization. As generalization conventional Markov decision processes (MDPs), MDPs augment state space, action reward structure include information. Accordingly, make conceptually easier connect typically used solve them – construct revise routes as new learned. anticipate will facilitate more scientific rigor studies, common language, allow better inquiry, improve classification description methods.

Language: Английский

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Enhanced intelligent water drops and cuckoo search algorithms for solving the capacitated vehicle routing problem

Information Sciences, Journal Year: 2015, Volume and Issue: 334-335, P. 354 - 378

Published: Dec. 1, 2015

Language: Английский

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