Approximation schemes for parallel machine scheduling with nonrenewable resources
Györgyi, Péter and Kis, Tamás (2017) Approximation schemes for parallel machine scheduling with nonrenewable resources. EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 258 (1). pp. 113123. ISSN 03772217 10.1016/j.ejor.2016.09.007

Text
Gyorgyi_113_3162930_ny.pdf Download (534kB)  Preview 

Text
Gyorgyi_113_3162930_z.pdf Restricted to Registered users only Download (595kB) 
Abstract
In this paper the approximability of parallel machine scheduling problems with resource consuming jobs is studied. In these problems, in addition to a parallel machine environment, there are nonrenewable resources, like raw materials, energy, or money, consumed by the jobs. Each resource has an initial stock, and some additional supplies at apriori known moments in time and in known quantities. The schedules must respect the resource constraints as well. The optimization objective is either the makespan, or the maximum lateness. Polynomial time approximation schemes are provided under various assumptions, and it is shown that the makespan minimization problem is APXcomplete if the number of machines is part of the input even if there are only two resources. © 2016 Elsevier B.V.
Item Type:  Article 

Uncontrolled Keywords:  Polynomial approximation; Resource Constraint; Polynomial time approximation schemes; Parallel machinescheduling problems; Parallel machine scheduling; Parallel machine; Nonrenewable resource; Makespan minimization; Approximation scheme; MACHINERY; Approximation theory; Scheduling; parallel machines; nonrenewable resources; approximation schemes; SUBJECT; COMPLEXITY; Algorithms; Approximability; CONSUMING JOBS; FINANCIAL CONSTRAINTS; INVENTORY CONSTRAINTS; Approximation schemes 
Subjects:  Q Science > QA Mathematics and Computer Science > QA75 Electronic computers. Computer science / számítástechnika, számítógéptudomány 
Divisions:  Research Laboratory on Engineering & Management Intelligence 
SWORD Depositor:  MTMT Injector 
Depositing User:  MTMT Injector 
Date Deposited:  21 Dec 2017 08:09 
Last Modified:  21 Jul 2019 13:50 
URI:  http://eprints.sztaki.hu/id/eprint/9279 
Update Item 