Single machine batch scheduling with two non-disjoint agents and splitable jobs

We investigate the scheduling problem on a single bounded parallel-batch machine where jobs belong to two non-disjoint agents (called agent A and agent B) and are of equal length but different size. Each job’s size can be arbitrarily split into two parts and processed in the consecutive batches. It...

Celý popis

Uložené v:
Podrobná bibliografia
Vydané v:Journal of combinatorial optimization Ročník 40; číslo 3; s. 774 - 795
Hlavní autori: Geng, Zhichao, Liu, Jiayu
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: New York Springer US 01.10.2020
Springer Nature B.V
Predmet:
Algorithms
Combinatorics
Completion time
Convex and Discrete Geometry
Mathematical Modeling and Industrial Mathematics
Mathematics
Mathematics and Statistics
Operations Research/Decision Theory
Optimization
Pareto optimum
Polynomials
Schedules
Scheduling
Theory of Computation
Splitable jobs
Polynomial-time algorithm
Parallel-batch
Pareto optimal
ISSN:1382-6905, 1573-2886
On-line prístup:Získať plný text
Tagy: Pridať tag
Žiadne tagy, Buďte prvý, kto otaguje tento záznam!
Popis
Shrnutí:We investigate the scheduling problem on a single bounded parallel-batch machine where jobs belong to two non-disjoint agents (called agent A and agent B) and are of equal length but different size. Each job’s size can be arbitrarily split into two parts and processed in the consecutive batches. It is permitted to process the jobs from different agents in a common batch. We show that it is unary NP-hard for the problem of minimizing the total weighted completion time of the jobs of agent A subject to the maximum cost of the jobs of agent B being upper bounded by a given threshold. For the case of the jobs of agent A having identical weights, we study the version of Pareto problem, and give a polynomial-time algorithm to generate all Pareto optimal points and a Pareto optimal schedule corresponding to each Pareto optimal point.
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:1382-6905
1573-2886
DOI:10.1007/s10878-020-00626-9