Hybrid algorithms for rich vehicle routing problems: a survey

Goel, Rajeev Kr.; Bansal, Sandhya

doi:10.1016/b978-0-12-815715-2.00011-7

Cited by 6 publications

(3 citation statements)

References 56 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…When multiple attributes are combined together, we obtain the so-called rich VRPs. A recent survey for rich variants was proposed by [7], who presented a literature review on hybrid methods and problems found, e.g., in food and newspaper distributions. The authors emphasized the importance of cooperative methods that combine exact and approximate algorithms and the proposal of benchmark problems, including real-life instances.…”

Section: Literature Reviewmentioning

confidence: 99%

See 1 more Smart Citation

An Optimization-Based Decision Support System for Multi-trip Vehicle Routing Problems

Cavecchia,

Alves de Queiroz,

Iori

et al. 2024

SN COMPUT. SCI.

View full text Add to dashboard Cite

Decision support systems (DSS) are used daily to make complex and hard decisions. Developing a DSS is not an easy task and may require combining different approaches to reach accurate and timely responses. In this paper, we present a DSS based on a micro-service architecture that we developed to handle a variant of the vehicle routing problem. The DSS has been implemented for a service company operating in the field of pharmaceutical distribution, and it helps decision-makers define the routes that different types of vehicles need to perform during the day to serve the customers' demands. The underlying optimization problem assumes that a vehicle can perform multiple routes daily and is constrained to operate within a given time horizon. Customers are characterized by hard time windows on the delivery times. The proposed DSS first handles geo-referencing and distance calculation tasks. Then, it invokes a two-step optimization approach in which vehicle routes are generated and combined to reduce the number of vehicles used. For the latter task, we propose and evaluate four solution methods: two greedy heuristics, a metaheuristic, and a mathematical model. All the methods are applied to solve real and randomly generated instances, showing that the metaheuristic algorithm is superior to the others in terms of solution quality and computing time. The company had a very positive feedback on the proposed DSS and is now using it to support its daily operations.

show abstract

Section: Literature Reviewmentioning

confidence: 99%

“…The objective function (7) asks to minimize the number of used vehicles on the day p. Constraints (8) impose that each route r is assigned to a given vehicle k if and only if k performs that route. Constraints (9) ensure that all routes are served by a vehicle.…”

Section: Mathematical Modelmentioning

confidence: 99%

An Optimization-Based Decision Support System for Multi-trip Vehicle Routing Problems

Cavecchia,

Alves de Queiroz,

Iori

et al. 2024

SN COMPUT. SCI.

View full text Add to dashboard Cite

show abstract

“…Moreover, Genetic algorithms have also been a significant tools for solving VRP problems (see [30,47]). A good classification of these methods is given in Goel and Bansal [19].…”

Section: Introductionmentioning

confidence: 99%

A new closed–open vehicle routing approach in stochastic environments

Rahmani

2020

International Journal of Computer Mathematics: Computer Systems

View full text Add to dashboard Cite

Collection and distribution of finished goods through cross-docking to predetermined customers or retailers are practical and challengeable mathematical modelling, optimization, and logistics problems. Thus, appropriate management of the transportation system can help companies decrease their costs and consequently earn more benefits. There is an abundance of modelling proposals in the literature. In this paper, a multi-cross-docking vehicle routing problem (MCVRP) is combined with close-open mixed vehicle routing problem (COMVRP) in the stochastic environment. It is assumed that the fleet of vehicles is heterogeneous. The objective is to minimize the total cost of serving customers. Since the travel time between retailer nodes is non-deterministic, a hybrid solution methodology is developed, which encompasses robust optimization, as well as firefly and genetic algorithm. Computational results demonstrate that the proposed algorithm can efficiently be used to solve the proposed model.

show abstract

Vehicle Routing and the VDI Directive 2700/Part 4 on Axle Weight Constraints

Schönberger

2021

Logistik in Wissenschaft Und Praxis

View full text Add to dashboard Cite

Hybrid algorithms for rich vehicle routing problems: a survey

Cited by 6 publications

References 56 publications

An Optimization-Based Decision Support System for Multi-trip Vehicle Routing Problems

An Optimization-Based Decision Support System for Multi-trip Vehicle Routing Problems

A new closed–open vehicle routing approach in stochastic environments

Vehicle Routing and the VDI Directive 2700/Part 4 on Axle Weight Constraints

Contact Info

Product

Resources

About