• 한국경영과학회지
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• 제35권1호
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• pp.47-65
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• 2010

In this study the artillery fire system is investigated in consideration of the characteristics of the troop and the target. Two kinds of decision are to be made on the target allocation with fire ammunition and the fire sequencing for the target with duties in charge. The objective is to minimize the completion time for all troops. Each target has the specified amount of load of fire, which can be accomplished by a single troop or the combination of the troops having different capabilities. Mathematical model is suggested, and the heuristic algorithm which yields a solution within a reasonable computation time is developed. The algorithm consists of iterative three steps : the initial solution generation, the division improvement, and the exchange improvement. The performance of the heuristic is evaluated through the computational experiment

• 한국국방경영분석학회지
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• 제29권2호
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• pp.61-80
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• 2003

A fire sequencing problem is considered. Fire sequencing problem is a kind of scheduling problem that seeks to minimize the overall time span under a result of weapon­target allocation problem. The assigned weapons should impact a target simultaneously and a weapon cannot transfer the firing against another target before all planned rounds are consumed. The computational complexity of the fire sequencing problem is strongly NP­complete even if the number of weapons is two, so it is difficult to get the optimal solution in a reasonable time by the mathematical programming approach. Therefore, a genetic algorithm is adopted as a solution method, in which the representation of the solution, crossover and mutation strategies are applied on a specific condition. Computational results using randomly generated data are presented. We compared the solutions given by CPLEX and the genetic algorithm. Above $7(weapon){\times}15(target)$ size problems, CPLEX could not solve the problem even if we take enough time to solve the problem since the required memory size increases dramatically as the number of nodes expands. On the other hand, genetic algorithm approach solves all experimental problems very quickly and gives good solution quality.

• 한국경영과학회지
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• 제28권3호
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• pp.123-134
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• 2003

Fire Sequencing Problem (FSP) is to find a sequence of targets, where there exist a number of targets with different time units required to fire. Because of the weapon's specifications and the size of the targets, several weapons may fire on the same targets, and the time units required on firing for each weapon may be different from each other. The objective is to minimize the completion time of firing for given number of targets. Mathematical formulation is given, and the heuristic algorithm based on the paring of targets in advance is suggested. Performance of the heuristic is evaluated by comparison of heuristic appeared in the literature through the computational experiments.

• 산업경영시스템학회지
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• 제35권2호
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• pp.37-44
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• 2012

This paper focuses on scheduling problems arising in the military. In planned artillery attack operations, a large number of threatening enemy targets should be destroyed to minimize fatal loss to the friendly forces. We consider a situation in which the number of available weapons is smaller than the number of targets. Therefore it is required to develop a new sequencing algorithm for the unplanned artillery attack operation. The objective is to minimize the total loss to the friendly forces from the targets, which is expressed as a function of the fire power potential, after artillery attack operations are finished. We develop an algorithm considering the fire power potential and the time required to destroy the targets. The algorithms suggested in this paper can be used in real artillery attack operations if they are modified slightly to cope with the practical situations.

• 한국국방경영분석학회지
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• 제31권2호
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• pp.28-44
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• 2005

The previous studies approach the field artillery fire scheduling problem as deterministic and do not explicitly include information on the potential scenario changes. Unfortunately, the effort used to optimize fire sequences and reduce the total time of engagement is often inefficient as the collected military intelligence changes. Instead of modeling the fire sequencing problem as deterministic model, we consider a stochastic artillery fire scheduling model and devise a solution methodology to integrate possible enemy attack scenarios in the evaluation of artillery fire sequences. The goal is to use that information to find robust solutions that withstand disruptions in a better way, Such an approach is important because we can proactively consider the effects of certain unique scheduling decisions. By identifying more robust schedules, cascading delay effects will be minimized. In this paper we describe our stochastic model for the field artillery fire sequencing problem and offer revised robust stochastic model which considers worst scenario first. The robust stochastic model makes the solution more stable than the general two-stage stochastic model and also reduces the computational cost dramatically. We present computational results demonstrating the effectiveness of our proposed method by EVPI, VSS, and Variances.

• Management Science and Financial Engineering
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• 제5권2호
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• pp.55-59
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• 1999

In this note, we introduce the Fire Sequencing Problem, which arises in military operations. Given m weapons, n fixed targets nad required duration of firing of the weapons on the targets, we want to determine the start time of firing on each target so that makespan is miniized while satisfying various operational constraints. We show that the decision problem of the Fire Sequencing problem is strongly NP-complete and remains strongly NP-complete even if the number of weapons is two. We also briefly discuss the results with respect to the complexities of several well-known scheduling models.

• 한국국방경영분석학회지
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• 제36권1호
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• pp.15-27
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• 2010

현대전에 있어서 대량의 화력, 신속한 기동력은 전승의 핵심요소이기 때문에 전쟁에서 승리하기 위해서는 이에 대한 과학적인 운용이 요구된다. 따라서 첨단기술을 이용한 치밀한 화력계획과 신속 정확한 타격으로 적에게 치명적인 피해를 줄 수 있어야 한다. 특히 사격이 작전개시 전에 미리 계획하여 수행하게 되는 경우는 표적별 사격 필요량에 의해 사격부대의 사격량을 할당함과 동시에 사격순서를 결정한 후 전체사격시간을 최소화함으로써 사격의 효과를 높일 수 있다. 따라서 본 연구에서는 이러한 사격완료시간을 최소화하기 위하여 동시에 표적을 타격하는 경우와 현재 야전부대에서 운용하고 있는 개별적으로 사격하는 문제 그리고 사격부대를 혼합하여 사격하는 경우의 최적의 사격완료시간을 비교하고, 사격시간 최소화를 위해 각 표적을 어떻게 할당할 것인지 수리모형을 이용하여 방안을 제시함으로써 작전계획에 맞는 사격계획표를 작성하는 것이다.

• 한국국방경영분석학회지
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• 제33권1호
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• pp.105-115
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• 2007

장차전은 첨단화된 무기체계와 최근의 전쟁양상을 고려해 볼 때 화력전의 성공여부가 전쟁의 결정적인 영향을 초래하게 될 것이다. 하지만 현재 한국군 포병전력은 수적으로 북한군에 비해 열세이며, 이를 극복하기 위한 방법으로 신속/정확한 사격으로 적에게 치명적인 피해를 줄 것이 요구된다. 따라서, 본 논문에서는 다수 표적을 수리적 모델을 이용하여 사격순서를 정하여 사격종료시간을 최소화함으로써 작전 운영의 융통성을 부여해 줄 수 있는 방법을 제시하였다. 또한 야전포병부대에서 화력계획 작성시 고려할 수 있는 지휘관의 의도, 일부 포병부대의 예상되는 사격제한(진지변환, 사거리 한계),우선순위 표적(핵심, 고가치), 화력계획의 차후 변경 등 각종 실질적 상황을 고려하여 최대한 빠른 시간에 사격을 마칠 수 있도록 하였다. 이와 같은 사격순서 결정문제를 혼합정수 계획모형(MIP: Mixed Integer Programming)으로 구성하였고 분석 수단으로 ILOG OPL을 이용하여 최적해를 구하였다. 본 연구에서 제시한 모형을 야전포병부대에서 활용한다면, 작전운용간 좀더 효과적이고 신속한 사격이 되어 전투력 향상에 기여할 수 있을 것이다.

• 산업경영시스템학회지
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• 제33권3호
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• pp.154-161
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• 2010

This paper considers the simultaneously firing model for the artillery operations. The objective of this paper is to find the optimal fire sequence minimizing the final completion time of the firing missions of multiple artillery units for multiple targets. In the problem analysis, we derive several solution properties to reduce the solution space. Moreover, two lower bounds of objective are derived and tested along with the derived properties within a branch-and-bound scheme. Two efficient heuristic algorithms are also developed. The overall performances of the proposed branch-and-bound and heuristic algorithms are evaluated through various numerical experiments.

• The Plant Pathology Journal
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• 제37권4호
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• pp.404-412
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• 2021

Despite the plant microbiota plays an important role in plant health, little is known about the potential interactions of the flower microbiota with pathogens. In this study, we investigated the microbial community of apple blossoms when infected with Erwinia amylovora. The long-read sequencing technology, which significantly increased the genome sequence resolution, thus enabling the characterization of fire blight-induced changes in the flower microbial community. Each sample showed a unique microbial community at the species level. Pantoea agglomerans and P. allii were the most predominant bacteria in healthy flowers, whereas E. amylovora comprised more than 90% of the microbial population in diseased flowers. Furthermore, gene function analysis revealed that glucose and xylose metabolism were enriched in diseased flowers. Overall, our results showed that the microbiome of apple blossoms is rich in specific bacteria, and the nutritional composition of flowers is important for the incidence and spread of bacterial disease.