1.

Record Nr.

UNINA9910728395403321

Autore

Sleptchenko Andrei

Titolo

Variable Neighborhood Search [[electronic resource] ] : 9th International Conference, ICVNS 2022, Abu Dhabi, United Arab Emirates, October 25–28, 2022, Revised Selected Papers / / edited by Andrei Sleptchenko, Angelo Sifaleras, Pierre Hansen

Pubbl/distr/stampa

Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023

ISBN

3-031-34500-2

Edizione

[1st ed. 2023.]

Descrizione fisica

1 online resource (159 pages)

Collana

Lecture Notes in Computer Science, , 1611-3349 ; ; 13863

Altri autori (Persone)

SifalerasAngelo

HansenPierre

Disciplina

519.3

Soggetti

Computer science—Mathematics

Discrete mathematics

Algorithms

Mathematics of Computing

Discrete Mathematics in Computer Science

Design and Analysis of Algorithms

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Nota di contenuto

A metaheuristic approach for solving Monitor Placement Problem -- A VNS-based heuristic for the minimum number of resources under a perfect schedule -- BVNS for Overlapping Community Detection -- A Simulation-Based Variable Neighborhood Search Approach for Optimizing Cross-Training Policies -- Multi-Objective Variable Neighborhood Search for improving software modularity -- An Effective VNS for Delivery Districting -- BVNS for the Minimum Sitting Arrangement problem in a cycle -- Assigning Multi-Skill Confgurations to Multiple Servers with a Reduced VNS -- Multi-Round Infuence Maximization: A Variable Neighborhood Search Approach -- A VNS based heuristic for a 2D Open Dimension Problem -- BVNS for the bi-objective multi row equal facility layout problem.

Sommario/riassunto

This volume constitutes the proceedings of the 9th International Conference on Variable Neighborhood Search, ICVNS 2023, held in Abu Dhabi, United Arab Emirates, in October 2022. The 11 full papers



presented in this volume were carefully reviewed and selected from 29 submissions. The papers describe recent advances in methods and applications of variable neighborhood search.