Online hierarchical scheduling: An approach using mathematical programming

This paper considers an online hierarchical scheduling problem on parallel identical machines. We are given a set of m machines and a sequence of jobs. Each machine has a different hierarchy, and each job also has a hierarchy associated with it. A job can be assigned to a machine only if its hierarc...

Celý popis

Uloženo v:
Podrobná bibliografie
Vydáno v:Theoretical computer science Ročník 412; číslo 3; s. 246 - 256
Hlavní autoři: Tan, Zhiyi, Zhang, An
Médium: Journal Article
Jazyk:angličtina
Vydáno: Oxford Elsevier B.V 21.01.2011
Elsevier
Témata:
Algorithms
Applied sciences
Competitive ratio
Computer science; control theory; systems
Computer systems performance. Reliability
Exact sciences and technology
Hierarchies
Hierarchy
Logic and foundations
Lower bounds
Mathematical logic, foundations, set theory
Mathematical models
Mathematical programming
Mathematics
Miscellaneous
Numerical analysis
Numerical analysis. Scientific computation
Numerical methods in mathematical programming
Numerical methods in mathematical programming, optimization and calculus of variations
On-line systems
Online
Recursion theory
Scheduling
Sciences and techniques of general use
Software
Theoretical computing
Hierarchy
Scheduling
Competitive ratio
Online
Mathematical programming
Lower bound
Computer theory
Optimal algorithm
Parallel machines
Makespan
Competitive algorithms
Bounded solution
Maximum
ISSN:0304-3975, 1879-2294
On-line přístup:Získat plný text
Tagy: Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
Popis
Shrnutí:This paper considers an online hierarchical scheduling problem on parallel identical machines. We are given a set of m machines and a sequence of jobs. Each machine has a different hierarchy, and each job also has a hierarchy associated with it. A job can be assigned to a machine only if its hierarchy is no less than that of the machine. The objective is to minimize the makespan, i.e., the maximum load of all machines. Two models are studied in the paper. For the fractional model, we present an improved algorithm and lower bounds. Both the algorithm and the lower bound are based on solutions of mathematical programming. For any given m , our algorithm is optimal by numerical calculation. For the integral model, we present both a general algorithm for any m , and an improved algorithm with better competitive ratios of 2.333 and 2.610 for m = 4 and 5, respectively.
Bibliografie:ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 23
ISSN:0304-3975
1879-2294
DOI:10.1016/j.tcs.2009.08.014