Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Research › peer-review
Irreducible Bin Packing : Complexity, Solvability and Application to the Routing Open Shop. / Chernykh, Ilya; Pyatkin, Artem.
Learning and Intelligent Optimization - 13th International Conference, LION 13, Revised Selected Papers. ed. / Nikolaos F. Matsatsinis; Yannis Marinakis; Panos Pardalos. Springer Gabler, 2020. p. 106-120 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11968 LNCS).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Research › peer-review
}
TY - GEN
T1 - Irreducible Bin Packing
T2 - 13th International Conference on Learning and Intelligent Optimization, LION 13
AU - Chernykh, Ilya
AU - Pyatkin, Artem
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 - We introduce the following version of an “inefficient” bin packing problem: maximize the number of bins under the restriction that the total content of any two bins is larger than the bin capacity. There is a trivial upper bound on the optimum in terms of the total size of the items. We refer to the decision version of this problem with the number of bins equal to the trivial upper bound as Irreducible Bin Packing. We prove that this problem is NP-complete in an ordinary sense and derive a sufficient condition for its polynomial solvability. The problem has a certain connection to a routing open shop problem which is a generalization of the metric TSP and open shop, known to be NP-hard even for two machines on a 2-node network. So-called job aggregation at some node of a transportation network can be seen as an instance of a bin packing problem. We show that for a two-machine case a positive answer to the Irreducible Bin Packing problem question at some node leads to a linear algorithm of constructing an optimal schedule subject to some restrictions on the location of that node.
AB - We introduce the following version of an “inefficient” bin packing problem: maximize the number of bins under the restriction that the total content of any two bins is larger than the bin capacity. There is a trivial upper bound on the optimum in terms of the total size of the items. We refer to the decision version of this problem with the number of bins equal to the trivial upper bound as Irreducible Bin Packing. We prove that this problem is NP-complete in an ordinary sense and derive a sufficient condition for its polynomial solvability. The problem has a certain connection to a routing open shop problem which is a generalization of the metric TSP and open shop, known to be NP-hard even for two machines on a 2-node network. So-called job aggregation at some node of a transportation network can be seen as an instance of a bin packing problem. We show that for a two-machine case a positive answer to the Irreducible Bin Packing problem question at some node leads to a linear algorithm of constructing an optimal schedule subject to some restrictions on the location of that node.
KW - Bin packing to the maximum
KW - Efficient normality
KW - Irreducible Bin Packing
KW - Job aggregation
KW - Polynomially solvable subcase
KW - Routing open shop
KW - Superoverloaded node
UR - http://www.scopus.com/inward/record.url?scp=85082401633&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-38629-0_9
DO - 10.1007/978-3-030-38629-0_9
M3 - Conference contribution
AN - SCOPUS:85082401633
SN - 9783030386283
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 106
EP - 120
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
Y2 - 27 May 2019 through 31 May 2019
ER -
ID: 23878267