Maximizing the performance of the Iraqi Armed Forces and determining the optimal path for them using the dynamic programming

Khalaf, Wakas S.; Shakir, Maitham Mouafq; Abd-Alreda, Nagham Yosif

doi:10.22075/ijnaa.2021.5465

Maximizing the performance of the Iraqi Armed Forces and determining the optimal path for them using the dynamic programming

Document Type : Research Paper

Authors

Wakas S. Khalaf ¹

Maitham Mouafq Shakir ²

Nagham Yosif Abd-Alreda ¹

¹ Department of Industrial Management, College of Administration and Economics, University of Baghdad, Iraq

² Studies and Planning Department, University of Baghdad, Iraq

10.22075/ijnaa.2021.5465

Abstract

The Iraqi Ministry of Defense decided that there would be no escape for the terrorist gang members from the death which it proceeded to it with a false doctrine until it is eradicated from Iraq which can never be an incubator of terrorism, accordingly and with the capabilities available to the ministry, the ministry has developed two strategies: The first is allocating ten regiments from the Iraqi Special Operations Forces (ISOF) to maximize the performance of the Iraqi armed forces (IAF) in defending the homeland and maintaining its security and stability from terrorist gangs in four border regions in Iraq. The second is to reduce the arrival time of the ISOF to the battlefield by determining the optimal possible paths using an efficient scientific approach which is the dynamic programming (DP). The results of this study after solving a real-life problem proved that the proposed approach is an effective mathematical approach for taking a series of related decisions by finding maximization level of performance of ISOF and the shortest time for them to reach the battlefield.

Keywords

Allocating, Maximizing the performance, Optimal path, Reducing arrival time, Dynamic programming

[1] Jenkins, P.R., Robbins, M.J., and Lunday, J.L. (2021) ‘Approximate dynamic programming for the military
aeromedical evacuation dispatching, preemption-rerouting, and redeployment problem’, European Journal of Operational Research. Vol. 290, No. 1, 1 April 2021, pp. 132-143.
[2] Hillier, F.S., and Lieberman, G.J. (2015) Introduction to Operations Research. 10th Ed, United States of America:
McGraw-Hill Education.
[3] Khalaf, W.S. Halem H.D. Finding the fuzzy maximum flow for Imam Al-Kadhim’ (AS) visitors using the fuzzy
dynamic programming method. JEAS. 2018 Oct 25; 24(103), 102-127.
[4] Khalaf ,W.S. (2021) Find the Optimal Allocation of Health Centers for some of the Villages in Baghdad Using
the Fuzzy Dynamic programming. Baghdad Science Journal, (In Press).
[5] Love, R.F. (1976) ‘Note-one-dimensional facility location-allocation using dynamic programming. Management
Science’ , Vol. 22, No. 5, pp. 614-617.
[6] Mahdavi, I., Nourifar, R., Heidarzade, A., and Amiri, N.M. (2009) ‘A dynamic programming approach for finding
the shortest chains in a fuzzy network’, Applied Soft Computing, Vol. 9, No. 2, pp. 503-511.
[7] Mafakheri, F., Breton, M., and Ghoniem, A. (2011) ‘Supplier selection-order allocation: A two-stage multiple
criteria dynamic programming approach’, International Journal of Production Economics, Vol. 132, No. 1, pp.
52-57.
[8] Mandal, M. and Venkataraman, S. (2019) ‘A dynamic programming model for perishable inventory management’,
International Journal of Operational Research, Vol. 35, No. 2, pp.147–177.
[9] Nemhauser, G.L., and Ullmann, Z. (1969) ‘Discrete dynamic programming and capital allocation’, Management
Science, Vol. 15, No. 9, pp. 494-505.
[10] Summers, D.S., Robbins, M.J., and Lunday, B.J. (2020) ‘An approximate dynamic programming approach for
comparing firing policies in a networked air defence environment’, Computers & Operations Research, Vol. 117,
104890.
[11] Taha, H.A. (2017). Operations Research: An Introduction, 10th Edition, Global Edition, Malaysia: Pearson
Education.
[12] Yu, S., Gao, S. and Sun, H. (2016) ‘A dynamic programming model for environmental investment decision-making
in coal mining’, Applied Energy, Vol. 166, pp. 273-281.