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학술논문경영과학2017.03 발행KCI 피인용 1

비계획 사격상황에서 적 위협 최소화를 위한 실시간 사격순서 결정 연구

Real-time Algorithms to Minimize the Threatening Probability in a Fire Scheduling Problem for Unplanned Artillery Attack Operation

차영호(육군분석평가단); 방준영(성결대학교); 심상오(한밭대학교)

34권 1호, 47~56쪽

초록

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.

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.

발행기관:
한국경영과학회
DOI:
http://dx.doi.org/10.7737/KMSR.2017.34.1.047
분류:
경영학

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비계획 사격상황에서 적 위협 최소화를 위한 실시간 사격순서 결정 연구 | 경영과학 2017 | AskLaw | 애스크로 AI