Результаты исследований: Публикации в книгах, отчётах, сборниках, трудах конференций › статья в сборнике материалов конференции › научная › Рецензирование
Efficient Algorithms for the Routing Open Shop with Unrelated Travel Times on Cacti. / Chernykh, Ilya; Krivonogova, Olga.
Optimization and Applications - 10th International Conference, OPTIMA 2019, Revised Selected Papers. ред. / Milojica Jaćimović; Michael Khachay; Vlasta Malkova; Mikhail Posypkin. Springer Gabler, 2020. стр. 1-15 (Communications in Computer and Information Science; Том 1145 CCIS).Результаты исследований: Публикации в книгах, отчётах, сборниках, трудах конференций › статья в сборнике материалов конференции › научная › Рецензирование
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TY - GEN
T1 - Efficient Algorithms for the Routing Open Shop with Unrelated Travel Times on Cacti
AU - Chernykh, Ilya
AU - Krivonogova, Olga
N1 - Publisher Copyright: © Springer Nature Switzerland AG 2020. Copyright: Copyright 2020 Elsevier B.V., All rights reserved.
PY - 2020/1/1
Y1 - 2020/1/1
N2 - The object of investigation is the routing open shop problem, in which a fleet of machines have to visit all the nodes of a given transportation network to perform operations on some jobs located at those nodes. Each machine has to visit each node, to process each job and to return back to the common initial location—the depot. Operations of each job can be processed in an arbitrary sequence, any machine may perform at most one operation at a time. The goal is to construct a feasible schedule to minimize the makespan. The routing open shop problem is known to be NP-hard even in the simplest two-machine case with the transportation network consisting of just two nodes (including the depot). We consider a certain generalization of this problem in which travel times are individual for each of the two machines and the structure of the transportation network is an arbitrary cactus. We generalize an instance reduction algorithm known for the problem on a tree with identical travel times, and use it to describe new polynomially solvable cases for the problem, as well as an efficient approximation algorithm for another special case with a tight approximation ratio guarantee.
AB - The object of investigation is the routing open shop problem, in which a fleet of machines have to visit all the nodes of a given transportation network to perform operations on some jobs located at those nodes. Each machine has to visit each node, to process each job and to return back to the common initial location—the depot. Operations of each job can be processed in an arbitrary sequence, any machine may perform at most one operation at a time. The goal is to construct a feasible schedule to minimize the makespan. The routing open shop problem is known to be NP-hard even in the simplest two-machine case with the transportation network consisting of just two nodes (including the depot). We consider a certain generalization of this problem in which travel times are individual for each of the two machines and the structure of the transportation network is an arbitrary cactus. We generalize an instance reduction algorithm known for the problem on a tree with identical travel times, and use it to describe new polynomially solvable cases for the problem, as well as an efficient approximation algorithm for another special case with a tight approximation ratio guarantee.
KW - Instance reduction
KW - Optima localization
KW - Polynomially solvable subcase
KW - Routing open shop
KW - Unrelated travel times
UR - http://www.scopus.com/inward/record.url?scp=85078428503&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-38603-0_1
DO - 10.1007/978-3-030-38603-0_1
M3 - Conference contribution
AN - SCOPUS:85078428503
SN - 9783030386023
T3 - Communications in Computer and Information Science
SP - 1
EP - 15
BT - Optimization and Applications - 10th International Conference, OPTIMA 2019, Revised Selected Papers
A2 - Jaćimović, Milojica
A2 - Khachay, Michael
A2 - Malkova, Vlasta
A2 - Posypkin, Mikhail
PB - Springer Gabler
T2 - 10th International Conference on Optimization and Applications, OPTIMA 2019
Y2 - 30 September 2019 through 4 October 2019
ER -
ID: 23260745