Efficient multiprocessor scheduling based on genetic algorithms

E. S.H. Hou; R. Hong; N. Ansari

Efficient multiprocessor scheduling based on genetic algorithms

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

An efficient method, based on genetic algorithms, for solving the multiprocessor scheduling problem is propsed. The representation of the search node is based on the schedule of the tasks in each individual processor. The genetic operator is based on the precedence relations between the tasks in the task graph. The genetic algorithm is applied to the problem of scheduling robot inverse dynamics computations.

Original language	English (US)
Title of host publication	Power Electronics Emerging Technologies
Publisher	Publ by IEEE
Pages	1239-1243
Number of pages	5
ISBN (Print)	0879426004
State	Published - 1990
Event	16th Annual Conference of IEEE Industrial Electronics Society - IECON'90 - Pacific Grove, CA, USA Duration: Nov 27 1990 → Nov 30 1990

Publication series

Name	IECON Proceedings (Industrial Electronics Conference)
Volume	2

Other

Other	16th Annual Conference of IEEE Industrial Electronics Society - IECON'90
City	Pacific Grove, CA, USA
Period	11/27/90 → 11/30/90

All Science Journal Classification (ASJC) codes

Control and Systems Engineering
Electrical and Electronic Engineering

Cite this

@inproceedings{3b88b64c33c344258ce1c1a49c98893c,

title = "Efficient multiprocessor scheduling based on genetic algorithms",

abstract = "An efficient method, based on genetic algorithms, for solving the multiprocessor scheduling problem is propsed. The representation of the search node is based on the schedule of the tasks in each individual processor. The genetic operator is based on the precedence relations between the tasks in the task graph. The genetic algorithm is applied to the problem of scheduling robot inverse dynamics computations.",

author = "Hou, {E. S.H.} and R. Hong and N. Ansari",

year = "1990",

language = "English (US)",

isbn = "0879426004",

series = "IECON Proceedings (Industrial Electronics Conference)",

publisher = "Publ by IEEE",

pages = "1239--1243",

booktitle = "Power Electronics Emerging Technologies",

note = "16th Annual Conference of IEEE Industrial Electronics Society - IECON'90 ; Conference date: 27-11-1990 Through 30-11-1990",

}

TY - GEN

T1 - Efficient multiprocessor scheduling based on genetic algorithms

AU - Hou, E. S.H.

AU - Hong, R.

AU - Ansari, N.

PY - 1990

Y1 - 1990

N2 - An efficient method, based on genetic algorithms, for solving the multiprocessor scheduling problem is propsed. The representation of the search node is based on the schedule of the tasks in each individual processor. The genetic operator is based on the precedence relations between the tasks in the task graph. The genetic algorithm is applied to the problem of scheduling robot inverse dynamics computations.

AB - An efficient method, based on genetic algorithms, for solving the multiprocessor scheduling problem is propsed. The representation of the search node is based on the schedule of the tasks in each individual processor. The genetic operator is based on the precedence relations between the tasks in the task graph. The genetic algorithm is applied to the problem of scheduling robot inverse dynamics computations.

UR - http://www.scopus.com/inward/record.url?scp=0025574879&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0025574879&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:0025574879

SN - 0879426004

T3 - IECON Proceedings (Industrial Electronics Conference)

SP - 1239

EP - 1243

BT - Power Electronics Emerging Technologies

PB - Publ by IEEE

T2 - 16th Annual Conference of IEEE Industrial Electronics Society - IECON'90

Y2 - 27 November 1990 through 30 November 1990

ER -

Efficient multiprocessor scheduling based on genetic algorithms

Abstract

Publication series

Other

All Science Journal Classification (ASJC) codes

Other files and links

Fingerprint

Cite this