The full text of this article


A new optimisation method for scheduling with ACO and GA
by Seyed Nima Mirabedini; Hassan Mina; Seyed Hossein Iranmanesh
International Journal of Fuzzy Computation and Modelling (IJFCM), Vol. 1, No. 2, 2014


Abstract: In this paper we consider project scheduling in critical condition and encountered project delays and defeat. Under such circumstances the project manager should make the best decision for the project to decrease incoming risks, costs, time and maintain the organisation reputation. So in order to deliver the project on time, the manager has to find the critical jobs among the tasks which are not scheduled yet. We have presented two new mathematical models for achieving minimum time and cost of the project and is implemented by ant colony optimisation (ACO) and genetic algorithm (GA). Project task duration is considered as fuzzy-stochastic variable under uncertainty model. We test these models with an information technology (IT) project in real world and illustrate our how model reduce completion time and cost of the project and they can be implemented as a good trade-off for the main goal of the project.


is only available to individual subscribers or to users at subscribing institutions.


Existing subscribers:

Go to Inderscience Online Journals to access the full text.


Pay per view:

If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Fuzzy Computation and Modelling (IJFCM):
Login with your Inderscience username and password:


    Username:        Password:         

Forgotten your password?


Want to subscribe?

A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.


If you still need assistance, please email