Korean Management Science Review (경영과학)

The Korean Operations Research and Management Science Society (한국경영과학회)
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Real-time Algorithms to Minimize the Threatening Probability in a Fire Scheduling Problem for Unplanned Artillery Attack Operation

비계획 사격상황에서 적 위협 최소화를 위한 실시간 사격순서 결정 연구

  • Cha, Young-Ho (Center for Army Analysis and Simulation) ;
  • Bang, June-Young (Department of Industrial and Management Engineering, Sungkyul University) ;
  • Shim, Sangoh (Department of Business Administration, Hanbat National University)
  • 차영호 (육군 분석평가단) ;
  • 방준영 (성결대학교 산업경영공학부) ;
  • 심상오 (국립한밭대학교 경영회계학과)
  • Received : 2017.02.10
  • Accepted : 2017.03.10
  • Published : 2017.03.31
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Abstract

We focus on the Real time Fire Scheduling Problem (RFSP), the problem of determining the sequence of targets to be fired at, for the objective of minimizing threatening probability to achieve tactical goals. In this paper, we assume that there are m available weapons to fire at n targets (> m) and the weapons are already allocated to targets. One weapon or multiple weapons can fire at one target and these fire operations should start simultaneously while the finish time of them may be different. We suggest mathematical modeling for RFSP and several heuristic algorithms. Computational experiments are performed on randomly generated test problems and results show that the suggested algorithms outperform the firing method which is generally adopted in the field artillery.

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References

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