Periodicity: Bi Annual.
Impact Factor:
SJIF:5.079 & GIF:0.416
Submission:Any Time
Publisher: IIR Groups
Language: English
Review Process:
Double Blinded

Paper Template
Copyright Form
Subscription Form
web counter
web counter

News and Updates

Author can submit their paper through online submission. Click here

Paper Submission -> Blind Peer Review Process -> Acceptance -> Publication.

On an average time is 3 to 5 days from submission to first decision of manuscripts.

Double blind review and Plagiarism report ensure the originality

IJCOA provides online manuscript tracking system.

Every issue of Journal of IJCOA is available online from volume 1 issue 1 to the latest published issue with month and year.

Paper Submission:
Any Time
Review process:
One to Two week
Journal Publication:
June / December

IJCOA special issue invites the papers from the NATIONAL CONFERENCE, INTERNATIONAL CONFERENCE, SEMINAR conducted by colleges, university, etc. The Group of paper will accept with some concession and will publish in IJCOA website. For complete procedure, contact us at

SCIA Journal Metrics

Published in:   Vol. 4 Issue 1 Date of Publication:   June 2015
Page(s):   30-34 Publisher:   Integrated Intelligent Research (IIR)
DOI:   10.20894/IJCOA. SAI : 2014SCIA316F0834

Generally the Flowshop Scheduling Problem (FSSP) is a production environment problem where a set of jobs has to visit a set of machines in the same order. In permutation flow shops the sequence of jobs is the same on all machines with the objective of minimizing the sum of completion timesusing Genetic Algorithm. A significant research effort has been devoted for sequencing jobs in a flowshop for minimizing the make span. No machine is allowed to remain idle when a job is ready for processing. This paper, describes the Permutation Flowshop Scheduling Problem (PFSSP)solved by using Genetic Algorithm (GA) to minimize the makespan. The basic concept of genetic algorithm is, that it is developed for finding near to optimalsolution for the minimum makespan of the jobs, machines permutation flowshop scheduling problem. It shows that the innovative genetic algorithm approach which provides competitive results for the solution of Permutation Flowshop Scheduling Problem.