Igor S. Litvinchev

dblp:45/2651 · DBLP profile ↗
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15ranked-venue papers
6as first author
5since 2021 · last 2024
0000-0002-1850-4755ORCID · verified

Domains — the database's venue-derived domains; a paper can count in several

Computer networks · 8 · 3 first-author · 3 since 2021Artificial intelligence and machine learning · 3 · 2 first-authorTheory of computation · 3 · 2 since 2021Databases, data management, data science and information retrieval · 2 · 2 first-authorHuman-computer interaction and ubiquitous computing · 1 · 1 first-author
YearPublicationVenuePosition
2024 Packing spheres with quasi-containment conditions
abstract
Abstract A novel sphere packing problem is introduced. A maximum number of spheres of different radii should be placed such that the spheres do not overlap and their centers fulfill a quasi-containment condition. The latter allows the spheres to lie partially outside the given cuboidal container. Moreover, specified ratios between the placed spheres of different radii must be satisfied. A corresponding mixed-integer nonlinear programming model is formulated. It enables the exact solution of small instances. For larger instances, a heuristic strategy is proposed, which relies on techniques for the generation of feasible points and the decomposition of open dimension problems. Numerical results are presented to demonstrate the viability of the approach.
Andreas Fischer 0004, Igor S. Litvinchev, Tatiana E. Romanova, Petro I. Stetsyuk, Georgiy Yaskov
J. Glob. Optim.2
2024 Packing Soft Convex Polygons in an Optimized Convex Container
Igor S. Litvinchev, Luis Infante, Tatiana E. Romanova, Alberto Martinez-Noa, Luis Gutierrez
Mob. Networks Appl.1
2024 Packing stretched convex polygons in an optimized rectangle
Julia A. Bennell, Igor S. Litvinchev, Aleksandr V. Pankratov, Tatiana E. Romanova
Wirel. Networks2
2023 Packing convex polygons in minimum-perimeter convex hulls
Josef Kallrath, Tatiana E. Romanova, Aleksandr V. Pankratov, Igor S. Litvinchev, Luis Infante
J. Glob. Optim.4
2022 Editorial: Digitization of Organizations: Towards a New Paradigm of Real-Time Systems
Igor S. Litvinchev, Tatiana E. Romanova
Mob. Networks Appl.1
2020 Editorial
Pandian Vasant, Gerhard-Wilhelm Weber, Igor S. Litvinchev
Comput. Intell.3
2020 Lagrangian Approach to Modeling Placement Conditions in Optimized Packing Problems
Igor S. Litvinchev, Tatiana E. Romanova, Rogelio Corrales-Diaz, Aned Esquerra-Arguelles, Alberto Martinez-Noa
Mob. Networks Appl.1
2020 Enhancing iris template matching with the optimal path method
Vladimir P. Novik, Ivan A. Matveev, Igor S. Litvinchev
Wirel. Networks3
2020 Packing ellipses in an optimized rectangular container
Aleksandr V. Pankratov, Tatiana E. Romanova, Igor S. Litvinchev
Wirel. Networks3
2020 Binary monkey algorithm for approximate packing non-congruent circles in a rectangular container
Rafael Torres-Escobar, Jose Antonio Marmolejo Saucedo, Igor S. Litvinchev
Wirel. Networks3
2020 Nature-inspired meta-heuristics approaches for charging plug-in hybrid electric vehicle
Pandian Vasant, Jose Antonio Marmolejo Saucedo, Igor S. Litvinchev, Román Rodríguez-Aguilar
Wirel. Networks3
2019 Packing ellipses in an optimized convex polygon
Aleksandr V. Pankratov, Tatiana E. Romanova, Igor S. Litvinchev
J. Glob. Optim.3
2016 Using Valid Inequalities and Different Grids in LP-Based Heuristic for Packing Circular Objects
Igor S. Litvinchev, Luis Infante, Edith Lucero Ozuna Espinosa
ACIIDS (2)1
2015 Using Different Norms in Packing Circular Objects
Igor S. Litvinchev, Luis Infante, Edith Lucero Ozuna Espinosa
ACIIDS (2)1
2010 Large-Scale Public R&D Portfolio Selection by Maximizing a Biobjective Impact Measure
abstract
This paper addresses R&D portfolio selection in social institutions, state-owned enterprises, and other nonprofit organizations which periodically launch a call for proposals and distribute funds among accepted projects. A nonlinear discontinuous bicriterion optimization model is developed in order to find a compromise between a portfolio quality measure and the number of projects selected for funding. This model is then transformed into a linear mixed-integer formulation to present the Pareto front. Numerical experiments with up to 25 000 projects competing for funding demonstrate a high computational efficiency of the proposed approach. The acceptance/rejection rules are obtained for a portfolio using the rough set methodology.
Igor S. Litvinchev, Fernando López Irarragorri, Ada M. Alvarez, Eduardo René Fernández-González
IEEE Trans. Syst. Man Cybern. Part A1