Deterministic and Robust Optimization Approach for Single Artillery Unit Fire Scheduling Problem
In this study, deterministic and robust optimization models for single artillery unit fire scheduling are developed to minimize the total enemy threat to friendly forces by considering the enemy target threat level, enemy target destruction time, and target firing preparation time simultaneously. Ma...
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| Format: | Article |
| Language: | English |
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MDPI AG
2017-10-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/7/10/1038 |
| _version_ | 1818446270179573760 |
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| author | Yong Baek Choi Suk Ho Jin Kyung Sup Kim |
| author_facet | Yong Baek Choi Suk Ho Jin Kyung Sup Kim |
| author_sort | Yong Baek Choi |
| collection | DOAJ |
| description | In this study, deterministic and robust optimization models for single artillery unit fire scheduling are developed to minimize the total enemy threat to friendly forces by considering the enemy target threat level, enemy target destruction time, and target firing preparation time simultaneously. Many factors in war environments are uncertain. In particular, it is difficult to evaluate the threat levels of enemy targets definitively. We consider the threat level of an enemy target to be an uncertain parameter and propose a robust optimization model that minimizes the total enemy threat to friendly forces. The robust optimization model represents a semi-infinite problem that has infinitely many constraints. Therefore, we reformulate the robust optimization model into a tractable robust counterpart formulation with a finite number of constraints. In the robust counterpart formulation with cardinality-constrained uncertainty, the conservativeness and robustness of the solution can be adjusted with an uncertainty degree, Γ. Further, numerical experiments are conducted to verify that the robust counterpart formulation with cardinality-constrained uncertainty can be made equivalent to the deterministic optimization model and the robust counterpart formulation with box uncertainty by setting Γ accordingly. |
| first_indexed | 2024-12-14T19:45:03Z |
| format | Article |
| id | doaj.art-24f4c1962e7e430aa651c55f6c9f7ee2 |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-12-14T19:45:03Z |
| publishDate | 2017-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-24f4c1962e7e430aa651c55f6c9f7ee22022-12-21T22:49:35ZengMDPI AGApplied Sciences2076-34172017-10-01710103810.3390/app7101038app7101038Deterministic and Robust Optimization Approach for Single Artillery Unit Fire Scheduling ProblemYong Baek Choi0Suk Ho Jin1Kyung Sup Kim2Department of Industrial Engineering, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul 03722, KoreaDepartment of Industrial Engineering, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul 03722, KoreaDepartment of Industrial Engineering, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul 03722, KoreaIn this study, deterministic and robust optimization models for single artillery unit fire scheduling are developed to minimize the total enemy threat to friendly forces by considering the enemy target threat level, enemy target destruction time, and target firing preparation time simultaneously. Many factors in war environments are uncertain. In particular, it is difficult to evaluate the threat levels of enemy targets definitively. We consider the threat level of an enemy target to be an uncertain parameter and propose a robust optimization model that minimizes the total enemy threat to friendly forces. The robust optimization model represents a semi-infinite problem that has infinitely many constraints. Therefore, we reformulate the robust optimization model into a tractable robust counterpart formulation with a finite number of constraints. In the robust counterpart formulation with cardinality-constrained uncertainty, the conservativeness and robustness of the solution can be adjusted with an uncertainty degree, Γ. Further, numerical experiments are conducted to verify that the robust counterpart formulation with cardinality-constrained uncertainty can be made equivalent to the deterministic optimization model and the robust counterpart formulation with box uncertainty by setting Γ accordingly.https://www.mdpi.com/2076-3417/7/10/1038deterministic optimizationrobust optimizationsingle artillery unit fire schedulingthreat level |
| spellingShingle | Yong Baek Choi Suk Ho Jin Kyung Sup Kim Deterministic and Robust Optimization Approach for Single Artillery Unit Fire Scheduling Problem Applied Sciences deterministic optimization robust optimization single artillery unit fire scheduling threat level |
| title | Deterministic and Robust Optimization Approach for Single Artillery Unit Fire Scheduling Problem |
| title_full | Deterministic and Robust Optimization Approach for Single Artillery Unit Fire Scheduling Problem |
| title_fullStr | Deterministic and Robust Optimization Approach for Single Artillery Unit Fire Scheduling Problem |
| title_full_unstemmed | Deterministic and Robust Optimization Approach for Single Artillery Unit Fire Scheduling Problem |
| title_short | Deterministic and Robust Optimization Approach for Single Artillery Unit Fire Scheduling Problem |
| title_sort | deterministic and robust optimization approach for single artillery unit fire scheduling problem |
| topic | deterministic optimization robust optimization single artillery unit fire scheduling threat level |
| url | https://www.mdpi.com/2076-3417/7/10/1038 |
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