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Variable Neighborhood Search: 6th International Conference, ICVNS 2018, Sithonia, Greece, October 47, 2018, Revised Selected Papers 2019 ed. [Pehme köide]

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  • Formaat: Paperback / softback, 315 pages, kõrgus x laius: 235x155 mm, kaal: 504 g, 26 Illustrations, color; 67 Illustrations, black and white; XI, 315 p. 93 illus., 26 illus. in color., 1 Paperback / softback
  • Sari: Lecture Notes in Computer Science 11328
  • Ilmumisaeg: 14-Mar-2019
  • Kirjastus: Springer Nature Switzerland AG
  • ISBN-10: 303015842X
  • ISBN-13: 9783030158422
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Variable Neighborhood Search: 6th International Conference, ICVNS 2018, Sithonia, Greece, October 47, 2018, Revised Selected Papers 2019 ed.Suurem pilt
  • Formaat: Paperback / softback, 315 pages, kõrgus x laius: 235x155 mm, kaal: 504 g, 26 Illustrations, color; 67 Illustrations, black and white; XI, 315 p. 93 illus., 26 illus. in color., 1 Paperback / softback
  • Sari: Lecture Notes in Computer Science 11328
  • Ilmumisaeg: 14-Mar-2019
  • Kirjastus: Springer Nature Switzerland AG
  • ISBN-10: 303015842X
  • ISBN-13: 9783030158422
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9783030158422.html
Märksõnad:
This book constitutes the refereed post-conference proceedings of the 6th International Conference on Variable Neighborhood Search, ICVNS 2018, held in Sithonia, Greece, in October 2018.





ICVNS 2018 received 49 submissions of which 23 full papers were carefully reviewed and selected.





VNS is a metaheuristic based on systematic changes in the neighborhood structure within a search for solving optimization problems and related tasks. The main goal of ICVNS 2018 was to provide a stimulating environment in which researchers coming from various scientific fields could share and discuss their knowledge, expertise, and ideas related to the VNS metaheuristic and its applications.
Improved variable neighbourhood search heuristic for quartet
clustering.- On the k-medoids model for semi-supervised clustering.-
Complexity and Heuristics for the Max Cut-Clique Problem.- A VNS approach to
solve multi-level capacitated lotsizing problem with backlogging.- How to
locate disperse obnoxious facility centers?.- Basic VNS algorithms for
solving the pollution location inventory routing problem.- Less is More: The
Neighborhood Guided Evolution Strategies convergence on some classic
neighborhood operators.- New VNS variants for the Online Order Batching
Problem.- An adaptive VNS and Skewed GVNS approaches for School Timetabling
Problems.- Finding balanced bicliques in bipartite graphs using Variable
Neighborhood Search.- General Variable Neighborhood Search for Scheduling
Heterogeneous Vehicles in Agriculture.- Detecting weak points in networks
using Variable Neighborhood Search.- A Variable neighborhood search with
integer programming  for the zero-one Multiple-Choice Knapsack Problem with
Setup .- A VNS-based Algorithm with Adaptive Local Search for Solving the
Multi-Depot Vehicle Routing Problem.- Skewed Variable Neighborhood Search
Method for the Weighted Generalized Regenerator Location Problem.- Using a
variable neighborhood search to solve the single processor scheduling problem
with time restrictions.- An Evolutionary Variable Neighborhood Descent for
addressing an electric VRP variant.- A Variable Neighborhood Descent
heuristic for the multi-quay Berth Allocation and Crane Assignment Problem
under availability constraints.- A Variable Neighborhood Search approach for
solving the Multidimensional Multi-way Number Partitioning Problem.- A
general variable neighborhood search with Mixed VND for the multi-Vehicle
multi-Covering Tour Problem.- A Hybrid Firefly - VNS Algorithm for the
Permutation Flowshop Scheduling Problem.- Studying the impact of perturbation
methods on the efficiency of GVNS for the ATSP.- A general variable
neighborhood searchalgorithm to solve vehicle routing problems with optional
visits.