• Title/Summary/Keyword: target problem

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Insight into an Structural Similarity in Stage of Similar Mathematical Problem Solving Process (유사 문제 해결에서 구조적 유사성의 인식)

  • Jun, Young-Bae;Roh, Eun-Hwan;Kang, Jeong-Gi
    • The Mathematical Education
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    • v.50 no.1
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    • pp.1-12
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    • 2011
  • It is the aim of this paper to study the target problem solving process in reference to the base problem. We observed closely how students solve the target problem in reference to the base problem. The students couldn't solve the target problem, although they succeed to find the base problem. This comes from failing to discover the structural similarity between the target problem and the base problem. Especially it is important to cognize the proper corresponding of primary components between the base problem and target problem. And there is sometimes a part component of the target problem equivalent to the base problem and the target problem can't be solved without the insight into this fact. Consequently, finding the base problem fail to reach solving the target problem without the insight into their structural similarity. We have to make efforts to have an insight into the structural similarity between the target problem and the base problem to solve the target problem.

A Continuous Network Design Model for Target-Oriented Transport Mode Choice Problem (목표지향 교통수단선택을 위한 연속형 교통망설계모형)

  • Im, Yong-Taek
    • Journal of Korean Society of Transportation
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    • v.27 no.6
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    • pp.157-166
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    • 2009
  • A network design problem (NDP) is to find a design parameter to optimize the performance of transportation system. This paper presents a modified NDP, called target-oriented NDP, which contains a target that we try to arrive in real world, and also proposes a solution algorithm. Unlike general NDP which seeks an optimal value to minimize or to maximize objective function of the system, in target-oriented NDP traffic manager or operator can set a target level prior and then try to find an optimal design variable to attain this goal. A simple example for mode choice problem is given to test the model.

Allocating CO2 Emission by Sector: A Claims Problem Approach (Claims problem을 활용한 부문별 온실가스 감축목표 분석)

  • Yunji Her
    • Environmental and Resource Economics Review
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    • v.31 no.4
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    • pp.733-753
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    • 2022
  • Korean government established the Nationally Determined Contribution (NDC) in 2015. After revising in 2019, the government updated an enhanced target at the end of last year. When the NDC is addressed, the emission targets of each sector, such as power generation, industry, and buildings, are also set. This paper analyzes the emission target of each sector by applying a claims problem or bankruptcy problem developed from cooperative game theory. The five allocation rules from a claims problem are introduced and the properties of each rule are considered axiomatically. This study applies the five rules on allocating carbon emission by sector under the NDC target and compares the results with the announced government target. For the power generation sector, the government target is set lower than the emissions allocated by the five rules. On the other hand, the government target for the industry sector is higher than the results of the five rules. In other sectors, the government's targets are similar to the results of the rule that allocates emissions in proportion to each claim.

A Genetic Algorithm Approach to the Fire Sequencing Problem

  • Kwon, O-Jeong
    • Journal of the military operations research society of Korea
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    • v.29 no.2
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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.

A Study on Passive Homing Trajectory for Maximizing Target Information (표적 정보량을 최대화하는 피동 호밍궤적에 관한 고찰)

  • Ra, Won-Sang;Shin, Hyo-Sang;Jung, Bo-Young;Whang, Ick-Ho
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.68 no.1
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    • pp.172-181
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    • 2019
  • This paper deals with the problem of generating the energy optimal trajectory which is intended to enhance the target tracking performance of a passive homing missile. Noticing that the essence of passive target tracking is the range estimation problem, the target information gathered by passive measurements can be readily analyzed by introducing the range estimator designed in line-of-sight(LOS) frame. Moreover, for the linear filter structure of the suggested range estimator, the cost function associated with the target information is clearly expressed as a function of the line-of-sight rate. Based on this idea, the optimal missile trajectory maximizing the target information is obtained by solving the saddle point problem for an indefinite quadratic cost which consists of the target information and the energy. It is shown that, different from the previous heuristic approaches, the guidance command producing the optimal passive homing trajectory is produced by the modified proportional navigation guidance law whose navigation constant is determined by the weighting coefficient for target information cost.

A MARKOV DECISION PROCESSES FORMULATION FOR THE LINEAR SEARCH PROBLEM

  • Balkhi, Z.T.;Benkherouf, L.
    • Journal of the Korean Operations Research and Management Science Society
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    • v.19 no.1
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    • pp.201-206
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    • 1994
  • The linear search problem is concerned with finding a hiden target on the real line R. The position of the target governed by some probability distribution. It is desired to find the target in the least expected search time. This problem has been formulated as an optimization problem by a number of authors without making use of Markov Decision Process (MDP) theory. It is the aim of the paper to give a (MDP) formulation to the search problem which we feel is both natural and easy to follow.

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Hierarchical Lazy Greedy Algorithm for Weapon Target Assignment (무기할당을 위한 계층적 레이지 그리디 알고리즘)

  • Jeong, Hyesun
    • Journal of the Korea Institute of Military Science and Technology
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    • v.23 no.4
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    • pp.381-388
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    • 2020
  • Weapon target assignment problem is an essential technology for automating the operator's rapid decision-making support in a battlefield situation. Weapon target assignment problem is a kind of the optimization problem that can build up an objective function by maximizing the number of threat target destructed or maximizing the survival rate of the protected assets. Weapon target assignment problem is known as the NP-Complete, and various studies have been conducted on it. Among them, a greedy heuristic algorithm which guarantees (1-1/e) approximation has been considered a very practical method in order to enhance the applicability of the real weapon system. In this paper, we formulated the weapon target assignment problem for supporting decision-making at the level of artillery. The lazy strategy based on hierarchical structure is proposed to accelerate the greedy algorithm. By experimental results, we show that our algorithm is more efficient in processing time and support the same level of the objective function value with the basic greedy algorithm.

A Study on Target Tracking Filter Architecture in Underwater Environment using Active and Passive Sensors (능, 수동센서를 이용한 수중환경에서의 표적추적필터 구조 연구)

  • Lim, Youngtaek;Suh, Taeil
    • Journal of the Korea Institute of Military Science and Technology
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    • v.18 no.5
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    • pp.517-524
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    • 2015
  • In this paper, we propose a new target tracking filter architecture using active and passive sensors in underwater environment. A passive sensor for target tracking needs a bearing measurement of target. And target tracking filter for using passive sensor has the observability problem. On the other hand, an active sensor does not have the problem associated with system observability problem because an active sensor uses bearing and range measurement. In this paper, the tracking filter algorithm that could be used in the active and passive sensor system is proposed to analyze maneuvering target and to improve target tracking performance. The proposed tracking filter algorithm is tested by a series of computer simulation runs and the results are analyzed and compared with existing algorithm.

A Faster Algorithm for Target Search (근사적 확률을 이용한 표적 탐색)

  • Jeong, Seong-Jin;Hong, Seong-Pil;Jo, Seong-Jin;Park, Myeong-Ju
    • Proceedings of the Korean Operations and Management Science Society Conference
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    • 2006.11a
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    • pp.57-59
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    • 2006
  • The purpose of search problem is to maximize the probability of target detection as limited search capability. Especially, as elapsing of time at a point of time of initial information received the target detection rate for searching an expected location due to a moving target such that wrecked ship or submarine decrease in these problems. The algorithm of search problem to a moving target having similar property of above targets should solve the search route as quickly as possible. In existing studies, they have a limit of applying in practice due to increasing computation time required by problem size (i.e., number of search area, search time). In this study, we provide that it takes more reasonable computation time than preceding studies even though extending a problem size practically using an approximate computation of probability.

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