Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Research › peer-review
Two-Machine Routing Open Shop: How Long Is the Optimal Makespan? / Chernykh, Ilya.
Mathematical Optimization Theory and Operations Research - 20th International Conference, MOTOR 2021, Proceedings. ed. / Panos Pardalos; Michael Khachay; Alexander Kazakov. Springer Science and Business Media Deutschland GmbH, 2021. p. 253-266 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 12755 LNCS).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Research › peer-review
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TY - GEN
T1 - Two-Machine Routing Open Shop: How Long Is the Optimal Makespan?
AU - Chernykh, Ilya
N1 - Funding Information: This research was supported by the program of fundamental scientific researches of the SB RAS No I.5.1., project No 0314-2019-0014, and by the Russian Foundation for Basic Research, projects 20-01-00045 and 20-07-00458. Publisher Copyright: © 2021, Springer Nature Switzerland AG.
PY - 2021
Y1 - 2021
N2 - We consider a routing open shop problem being a natural generalization of the metric TSP and the classic open shop scheduling problem. The maximal possible ratio of the optimal makespan and the standard lower bound for the routing open shop has already been investigated in the last few years. The two-machine case is mostly covered. It is constructively proven in 2013 that the ratio mentioned above cannot be greater than 4/3, however, we do not know of any problem instance with the value of that ratio greater than 6/5. The latter ratio is achievable for a simplest case with two nodes. On the other hand, it is known that optimal makespan is at most 6/5 of the standard lower bound for at least a few special cases of the transportation network: one is with at most three nodes, and another is a tree. In this paper, we introduce an ultimate instance reduction technique, which allows reducing the general problem into a case with at most four nodes and at most six jobs. As a by-product, we propose a new polynomially solvable case of the two-machine routing open shop problem.
AB - We consider a routing open shop problem being a natural generalization of the metric TSP and the classic open shop scheduling problem. The maximal possible ratio of the optimal makespan and the standard lower bound for the routing open shop has already been investigated in the last few years. The two-machine case is mostly covered. It is constructively proven in 2013 that the ratio mentioned above cannot be greater than 4/3, however, we do not know of any problem instance with the value of that ratio greater than 6/5. The latter ratio is achievable for a simplest case with two nodes. On the other hand, it is known that optimal makespan is at most 6/5 of the standard lower bound for at least a few special cases of the transportation network: one is with at most three nodes, and another is a tree. In this paper, we introduce an ultimate instance reduction technique, which allows reducing the general problem into a case with at most four nodes and at most six jobs. As a by-product, we propose a new polynomially solvable case of the two-machine routing open shop problem.
KW - Efficient algorithm
KW - Instance reduction
KW - Optima localization
KW - Routing open shop
KW - Standard lower bound
UR - http://www.scopus.com/inward/record.url?scp=85111407457&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-77876-7_17
DO - 10.1007/978-3-030-77876-7_17
M3 - Conference contribution
AN - SCOPUS:85111407457
SN - 9783030778750
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 253
EP - 266
BT - Mathematical Optimization Theory and Operations Research - 20th International Conference, MOTOR 2021, Proceedings
A2 - Pardalos, Panos
A2 - Khachay, Michael
A2 - Kazakov, Alexander
PB - Springer Science and Business Media Deutschland GmbH
T2 - 20th International Conference on Mathematical Optimization Theory and Operations Research, MOTOR 2021
Y2 - 5 July 2021 through 10 July 2021
ER -
ID: 34146618