Результаты исследований: Публикации в книгах, отчётах, сборниках, трудах конференций › статья в сборнике материалов конференции › научная › Рецензирование
Asymptotically Optimal Algorithms for the Prize-Collecting Traveling Salesman Problem on Random Inputs. / Gimadi, Edward Kh; Tsidulko, Oxana.
Learning and Intelligent Optimization - 13th International Conference, LION 13, Revised Selected Papers. ред. / Nikolaos F. Matsatsinis; Yannis Marinakis; Panos Pardalos. Springer Gabler, 2020. стр. 201-207 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Том 11968 LNCS).Результаты исследований: Публикации в книгах, отчётах, сборниках, трудах конференций › статья в сборнике материалов конференции › научная › Рецензирование
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TY - GEN
T1 - Asymptotically Optimal Algorithms for the Prize-Collecting Traveling Salesman Problem on Random Inputs
AU - Gimadi, Edward Kh
AU - Tsidulko, Oxana
N1 - Publisher Copyright: © 2020, Springer Nature Switzerland AG. Copyright: Copyright 2020 Elsevier B.V., All rights reserved.
PY - 2020/1/22
Y1 - 2020/1/22
N2 - The Prize-Collecting Traveling Salesman Problem is a class of generalizations of the classic Traveling Salesman Problem (TSP) where it is not necessary to visit all the vertices. Given the edge costs and a certain profit associated with each vertex, the goal is to find a route which satisfies maximum collected profit and minimum traveling costs constraints. We show polynomial-time approximation algorithms for two variants of the problem and establish conditions under which the presented algorithms are asymptotically optimal on random inputs.
AB - The Prize-Collecting Traveling Salesman Problem is a class of generalizations of the classic Traveling Salesman Problem (TSP) where it is not necessary to visit all the vertices. Given the edge costs and a certain profit associated with each vertex, the goal is to find a route which satisfies maximum collected profit and minimum traveling costs constraints. We show polynomial-time approximation algorithms for two variants of the problem and establish conditions under which the presented algorithms are asymptotically optimal on random inputs.
KW - Asymptotically optimal algorithm
KW - NP-hard problem
KW - Prize-collecting TSP
KW - Random inputs
UR - http://www.scopus.com/inward/record.url?scp=85082389095&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-38629-0_16
DO - 10.1007/978-3-030-38629-0_16
M3 - Conference contribution
AN - SCOPUS:85082389095
SN - 9783030386283
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 201
EP - 207
BT - Learning and Intelligent Optimization - 13th International Conference, LION 13, Revised Selected Papers
A2 - Matsatsinis, Nikolaos F.
A2 - Marinakis, Yannis
A2 - Pardalos, Panos
PB - Springer Gabler
T2 - 13th International Conference on Learning and Intelligent Optimization, LION 13
Y2 - 27 May 2019 through 31 May 2019
ER -
ID: 23892780