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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.

Online publication date: Tue, 27-Jan-2015

 

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