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MPM Job Scheduling Problem: a bi-objective approach

Authors: 

Dimitrios Tselios, Ilias Savvas, Tahar Kechadi

Publication Type: 
Refereed Original Article
Abstract: 
This paper presents a Recurrent Neural Network approach for the multipurpose machines Job Shop Scheduling Problem. This case of JSSP can be utilized for the modelling of project portfolio management besides the well known adop- tion in factory environment. Therefore, each project oriented organization develops a set of projects and it has to schedule them as a whole. In this work, we extended a bi-objective system model based on the JSSP modelling and formulated it as a combination of two recurrent neural networks. In addition, we designed an example within its neural networks that are focused on the Makespan and the Total Weighted Tardiness objectives. Moreover, we present the findings of our approach using a set of well known benchmark instances and the discussion about them and the singularity that arises
Digital Object Identifer (DOI): 
10.na
ISSN: 
1473-804x online, 1473-8031
Publication Status: 
Published
Publication Date: 
15/07/2014
Journal: 
Internation Journal of Simulation Systems, Science & Technology (IJSSST) V14,2014
Volume: 
14
Institution: 
National University of Ireland, Dublin (UCD)
Open access repository: 
No
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