Defensive Future Studies

Defensive Future Studies

Modeling the positioning of support forces in future battles using data envelopment analysis and the principles of natural and managerial accessibility

Document Type : Original Article

Authors
1 Assistant Professor of Industrial Engineering, IRI Military Command and Staff University, Tehran, Iran
2 Associate Professor of Operations Research, IRI Military Command and Staff University, Tehran. Iran
3 Assistant Professor of Industrial Engineering, IRI Military Command and Staff University, Tehran. Iran
Abstract
Objective: In this paper, a mathematical modeling is presented to determine efficient locations for deployment of support forces using data envelopment analysis.
Methodology: The proposed model has the possibility to first change the manageable inputs in order to improve the outputs according to the principle of managerial accessibility and also if it is not possible to reduce the unmanageable inputs according to the principle of natural accessibility, it keeps them at least at the existing level. Therefore, the most important innovation and contribution of the present research is the modeling of the positioning of the support forces to support the ground forces in future battles, which is created by using data envelopment analysis and the simultaneous use of natural and managerial accessibility principles.
Findings: The intended model has been used to evaluate 25 potential locations that are ready to provide ground support services to help local forces in the disputed area so that the fire of war ends in favor of local forces. Finally, by providing a sensitivity analysis on the manageable input values, the maximum possible changes in the value of this type of input for each of the locations are specified.
Conclusion: The results of this research are of great importance considering the conditions raised in making and the effectiveness of commanders' decisions in order to locate support forces in future battles.
Keywords

Subjects


  • Amirteimoori, A., Mehdizadeh, S., & Kordrostami, S. (2022). Stochastic performance measurement in two-stage network processes: A data envelopment analysis approach. Kybernetika, 58(2), 200-217. DOI: 14736/kyb-2022-2-0200
  • Amirteimoori, A., Allahviranloo, T., Kordrostami, S., & Bagheri, S. F. (2023). Improving decision-making units in performance analysis methods: a data envelopment analysis approach. Mathematical Sciences, 1-11. DOI: 1007/s40096-023-00488-8
  • Arana-Jiménez, M., Sánchez-Gil, M. C., Younesi, A., & Lozano, S. (2021). Integer interval DEA: An axiomatic derivation of the technology and an additive, slacks-based model. Fuzzy sets and systems, 422, 83-105. DOI: 1016/j.fss.2021.02.013
  • Asadi, F., Kordrostami, S., Amirteimoori, A., & Bazrafshan, M. (2023). Inverse data envelopment analysis without convexity: double frontiers. Decisions in Economics and Finance, 46(1), 335-354. DOI: 1007/s10203-023-00394-0
  • Bigdeli, H. and Mousazadeh, M. (2023). Analytical Hierarchy Process in modeling and solving matrix games in neutrosophic environment and its application in military problems. Military Science and Tactics19(64), 5-33. [in persian] DOI: 22034/qjmst.2023.544038.1627
  • Cao, J. X., Wang, X., & Gao, J. (2021). A two-echelon location-routing problem for biomass logistics systems. Biosystems engineering, 202, 106-118. DOI: 1016/j.biosystemseng.2020.12.008
  • Cheng, C., Zhu, R., Costa, A. M., Thompson, R. G., & Huang, X. (2021). Multi-period two-echelon location routing problem for disaster waste clean-up. Transportmetrica A: Transport Science, 1-31. DOI: 1080/23249935.2021.1990129
  • Ejabi, Ebrahim, and Pakneit, Abbas. (2023). "Performance Evaluation of Engineering Groups of the Islamic Republic of Iran Army Ground Forces in Relief Operations Against Floods and Earthquakes." Quarterly Journal of War Studies, 5(17), 35-62. [in persian]  DOI: 22034/qjws.2023.1989551.1113
  • Du, J., Wang, X., Wu, X., Zhou, F., & Zhou, L. (2022). Multi-objective optimization for two-echelon joint delivery location routing problem considering carbon emission under online shopping. Transportation Letters, 1-19. DOI: 1080/19427867.2022.2091669
  • Fakhr Mousavi, S. M., Amirteimoori, A., Kordrostami, S., & Vaez-Ghasemi, M. (2023). Non-radial two-stage network DEA model to estimate returns to scale. Journal of Modelling in Management, 18(1), 36-60. DOI: 1108/JM2-03-2021-0066
  • Fallahtafti, A., Ardjmand, E., Young II, W. A., & Weckman, G. R. (2021). A multi-objective two-echelon location-routing problem for cash logistics: A metaheuristic approach. Applied Soft Computing, 111, 107685. DOI: 1016/j.asoc.2021.107685
  • Gandra, V. M. S., Çalık, H., Wauters, T., Toffolo, T. A., Carvalho, M. A. M., & Berghe, G. V. (2021). The impact of loading restrictions on the two-echelon location routing problem. Computers & Industrial Engineering, 160, 107609. DOI: 1016/j.cie.2021.107609
  • Hasanpour Jesri, Z. S., Eshghi, K., Rafiee, M., & Van Woensel, T. (2022). The Multi-Depot Traveling Purchaser Problem with Shared Resources. Sustainability, 14(16), 10190. DOI: 3390/su141610190
  • He, D., Ceder, A. A., Zhang, W., Guan, W., & Qi, G. (2023). Optimization of a rural bus service integrated with e-commerce deliveries guided by a new sustainable policy in China. Transportation Research Part E: Logistics and Transportation Review, 172, 103069. DOI: 1016/j.tre.2023.103069
  • Heidari, A., Imani, D. M., Khalilzadeh, M., & Sarbazvatan, M. (2022). Green two-echelon closed and open location-routing problem: application of NSGA-II and MOGWO metaheuristic approaches. Environment, Development and Sustainability, 1-37. DOI: 1007/s10668-022-02646-6
  • Heydari Kushalshah, T., Daneshmand-Mehr, M., & Abolghasemian, M. (2023). Hybrid modelling for urban water supply system management based on a bi-objective mathematical model and system dynamics: A case study in Guilan province. Journal of Industrial and Systems Engineering, 15(1), 260-279. URL: http://www.jise.ir/article_148592.html
  • Hosseinzadeh Lotfi, F., Jahanshahloo, G. R., Khodabakhshi, M., Rostamy-Malkhlifeh, M., Moghaddas, Z., & Vaez-Ghasemi, M. (2013). A review of ranking models in data envelopment analysis. Journal of Applied Mathematics, 2013. DOI: 1155/2013/492421
  • Huang, N., Li, J., Zhu, W., & Qin, H. (2021). The multi-trip vehicle routing problem with time windows and unloading queue at depot. Transportation Research Part E: Logistics and Transportation Review, 152, 102370. DOI: 1016/j.tre.2021.102370
  • Jahani Sayyad Noveiri, M., & Kordrostami, S. (2023). Estimating sustainability dimensions using fuzzy inverse directional distance model with flexible measures: a health sector application. Soft Computing, 1-17. DOI: 1007/s00500-023-08243-0
  • Jiao, L., Peng, Z., Xi, L., Guo, M., Ding, S., & Wei, Y. (2022). A multi-stage heuristic algorithm based on task grouping for vehicle routing problem with energy constraint in disasters. Expert Systems with Applications, 118740. DOI: 1016/j.eswa.2022.118740
  • Kordrostami, S., Amirteimoori, A., & Noveiri, M. J. S. (2019). Inputs and outputs classification in integer-valued data envelopment analysis. Measurement, 139, 317-325. DOI: 1016/j.measurement.2019.03.004
  • Mohamed, I. B., Klibi, W., Sadykov, R., Şen, H., & Vanderbeck, F. (2022). The two-echelon stochastic multi-period capacitated location-routing problem. European Journal of Operational Research. DOI: 1016/j.ejor.2022.06.058
  • Nedjati, A., Izbirak, G., & Arkat, J. (2017). Bi-objective covering tour location routing problem with replenishment at intermediate depots: Formulation and meta-heuristics. Computers & Industrial Engineering, 110, 191-206. DOI: 1016/j.cie.2017.06.004
  • Neira, D. A., Aguayo, M. M., De la Fuente, R., & Klapp, M. A. (2020). New compact integer programming formulations for the multi-trip vehicle routing problem with time windows. Computers & Industrial Engineering, 144, 106399. DOI: 1016/j.cie.2020.106399
  • Nozari, H., Tavakkoli-Moghaddam, R., & Gharemani-Nahr, J. (2022). A neutrosophic fuzzy programming method to solve a multi-depot vehicle routing model under uncertainty during the covid-19 pandemic. International Journal of Engineering, 35(2), 360-371. DOI: 5829/ije.2022.35.02b.11
  • Shamami, N. , Mehdizadeh, E. , Yazdani, M. and Etebari, F. (2022). Proposing a Stackelberg mathematical model for weapon-target assignment considering both air and ground attacks. Military Science and Tactics18(59), 245-270. DOI: 22034/qjmst.2022.543952.1628
  • Pirabán-Ramírez, A., Guerrero-Rueda, W. J., & Labadie, N. (2022). The multi-trip vehicle routing problem with increasing profits for the blood transportation: An iterated local search metaheuristic. Computers & Industrial Engineering, 170, 108294. DOI: 1016/j.cie.2022.108294
  • Pourmohammadreza, N., & Jokar, M. R. A. (2023). A Novel Two-Phase Approach for Optimization of the Last-Mile Delivery Problem with Service Options. Sustainability, 15(10), 8098. DOI: 3390/su15108098
  • Rezaei Kallaj, M., Abolghasemian, M., Moradi Pirbalouti, S., Sabk Ara, M., & Pourghader Chobar, A. (2021). Vehicle routing problem in relief supply under a crisis condition considering blood types. Mathematical Problems in Engineering, 2021. DOI: 1155/2021/7216987
  • Wang, Y., Sun, Y., Guan, X., Fan, J., Xu, M., & Wang, H. (2021). Two-echelon multi-period location routing problem with shared transportation resource. Knowledge-Based Systems, 226, 107168. DOI: 1016/j.knosys.2021.107168
  • Wang, Y., Zhe, J., Wang, X., Sun, Y., & Wang, H. (2022). Collaborative Multidepot Vehicle Routing Problem with Dynamic Customer Demands and Time Windows. Sustainability, 14(11), 6709. DOI: 3390/su14116709
  • Xue, G., Wang, Y., Guan, X., & Wang, Z. (2022). A combined GA-TS algorithm for two-echelon dynamic vehicle routing with proactive satellite stations. Computers & Industrial Engineering, 164, 107899. DOI: 1016/j.cie.2021.107899
  • Yazdi, M., Golilarz, N. A., Adesina, K. A., & Nedjati, A. (2021). Probabilistic risk analysis of process systems considering epistemic and aleatory uncertainties: a comparison study. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 29(02), 181-207. DOI: 1142/S0218488521500089
  • Yu, X., Zhou, Y., & Liu, X. F. (2020). The two-echelon multi-objective location routing problem inspired by realistic waste collection applications: The composable model and a metaheuristic algorithm. Applied Soft Computing, 94, 106477. DOI: 1016/j.asoc.2020.106477