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:: Volume 3, Issue 3 (11-2016) ::
2016, 3(3): 1391-1412 Back to browse issues page
The Combinatorial Multi-Mode Resource Constrained Multi-Project Scheduling Problem
Denis Pinha * 1, Rashpal Ahluwalia2 , Pedro Senna3
1- West Virginia University, Morgantown, WV, USA , deniscruzpinha@gmail.com
2- West Virginia University, Morgantown, WV, USA
3- Federal Center for Technological Education of Rio de Janeiro, Rio de Janeiro, Brazil
Abstract:   (4228 Views)
This paper presents the formulation and solution of the Combinatorial Multi-Mode Resource Constrained Multi-Project Scheduling Problem. The focus of the proposed method is not on finding a single optimal solution, instead on presenting multiple feasible solutions, with cost and duration information to the project manager. The motivation for developing such an approach is due in part to practical situations where the definition of optimal changes on a regular basis. The proposed approach empowers the project manager to determine what is optimal, on a given day, under the current constraints, such as, change of priorities, lack of skilled worker. The proposed method utilizes a simulation approach to determine feasible solutions, under the current constraints. Resources can be non-consumable, consumable, or doubly constrained. The paper also presents a real-life case study dealing with scheduling of ship repair activities.
Keywords: Resource Constrained Project Scheduling, Mathematical Formulation, Discrete Event Simulation, Decision Support System
     
Type of Study: مقاله پژوهشی |
ePublished: 2017/09/28
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Pinha D, Ahluwalia R, Senna P. The Combinatorial Multi-Mode Resource Constrained Multi-Project Scheduling Problem. Journal title 2016; 3 (3) :1391-1412
URL: http://system.khu.ac.ir/ijsom/article-1-2707-en.html


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Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Volume 3, Issue 3 (11-2016) Back to browse issues page
International Journal of Supply and Operations Management International Journal of Supply and Operations Management
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