Please use this identifier to cite or link to this item: http://elar.urfu.ru/handle/10995/131099
Title: Approximation Schemes for Capacity Vehicle Routing Problems: A Survey
Authors: Chen, Y.
Issue Date: 2023
Publisher: Institute of Electrical and Electronics Engineers Inc.
Citation: Chen, Y 2023, Approximation Schemes for Capacity Vehicle Routing Problems: A Survey. в Proceedings - 2023 2nd International Conference on Computational Modelling, Simulation and Optimization, ICCMSO 2023: book. Institute of Electrical and Electronics Engineers Inc., стр. 277-282, 2023 2nd International Conference on Computational Modelling, Simulation and Optimization (ICCMSO), 23/06/2023. https://doi.org/10.1109/ICCMSO59960.2023.00059
Chen, Y. (2023). Approximation Schemes for Capacity Vehicle Routing Problems: A Survey. в Proceedings - 2023 2nd International Conference on Computational Modelling, Simulation and Optimization, ICCMSO 2023: book (стр. 277-282). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICCMSO59960.2023.00059
Abstract: The Capacity Vehicle Routing Problem (CVRP) pertains to the combinatorial optimization problem of identifying the optimal route for vehicles with a capacity constraint of k to travel from the depots to customers, which minimizes the total distance traveled. The Capacitated Vehicle Routing Problem (CVRP), which is essential to modelling logistics networks, has drawn a lot of interest in the field of combinatorial optimization. It has been established that the CVRP (Capacitated Vehicle Routing Problem) with a value of k greater than or equal to three exhibits computational complexity that is classified as NP-hard. Furthermore, it has been established that the problem is APXhard. It has been previously established that the solution is not approximatable in a metric space. Furthermore, this constitutes the principal challenge among the array of issues that confront Arora's approximation algorithm. The outstanding matter concerns the presence of a (1+$\epsilon$) PTAS (polynomial time approximation scheme) for the capacity vehicle routing problem in Euclidean space, regardless of the vehicle's capacity. The objective of this manuscript is to furnish a thorough and all-encompassing survey of the research progressions in the domain, encompassing the evolution of the field from its inception to the most recent cutting-edge discoveries. © 2023 IEEE.
Keywords: APPROXIMATION ALGORITHMS
CAPACITY VEHICLE ROUTING PROBLEMS
COMBINATORIAL OPTIMIZATION
POLYNOMIAL-TIME APPROXIMATION SCHEME
APPROXIMATION ALGORITHMS
POLYNOMIAL APPROXIMATION
ROUTING ALGORITHMS
VEHICLE ROUTING
VEHICLES
APPROXIMATION SCHEME
CAPACITATED VEHICLE ROUTING PROBLEM
CAPACITY CONSTRAINTS
CAPACITY VEHICLE ROUTING PROBLEMS
CLASSIFIEDS
COMBINATORIAL OPTIMIZATION PROBLEMS
LOGISTICS NETWORK
OPTIMAL ROUTES
POLYNOMIAL TIME APPROXIMATION SCHEMES
TOTAL DISTANCES
COMBINATORIAL OPTIMIZATION
URI: http://elar.urfu.ru/handle/10995/131099
Access: info:eu-repo/semantics/openAccess
Conference name: 2nd International Conference on Computational Modelling, Simulation and Optimization, ICCMSO 2023
Conference date: 23 June 2023 through 25 June 2023
SCOPUS ID: 85181172283
PURE ID: 50622584
ISBN: 9798350326666
DOI: 10.1109/ICCMSO59960.2023.00059
Appears in Collections:Научные публикации ученых УрФУ, проиндексированные в SCOPUS и WoS CC

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