• Journal of the military operations research society of Korea
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• v.31 no.2
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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.

• Korean Management Science Review
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• v.34 no.1
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• pp.47-56
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• 2017

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.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.1
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• pp.143-150
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• 2019

We focus on the weapon target assignment and fire scheduling problem (WTAFSP) with the objective of minimizing the makespan, i.e., the latest completion time of a given set of firing operations. In this study, we assume that there are m available weapons to fire at n targets (> m). The artillery attack operation consists of two steps of sequential procedure : assignment of weapons to the targets; and scheduling firing operations against the targets that are assigned to each weapon. This problem is a combination of weapon target assignment problem (WTAP) and fire scheduling problem (FSP). To solve this problem, we define the problem with a mixed integer programming model. Then, we develop exact algorithms based on a dynamic programming technique. Also, we suggest how to find lower bounds and upper bounds to a given problem. To evaluate the performance of developed exact algorithms, computational experiments are performed on randomly generated problems. From the results, we can see suggested exact algorithm solves problems of a medium size within a reasonable amount of computation time. Also, the results show that the computation time required for suggested exact algorithm can be seen to increase rapidly as the problem size grows. We report the result with analysis and give directions for future research for this study. This study is meaningful in that it suggests an exact algorithm for a more realistic problem than existing researches. Also, this study can provide a basis for developing algorithms that can solve larger size problems.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.4
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• pp.132-141
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• 2015

We focus on the fire scheduling problem (FSP), the problem of determining the sequence of targets to be fired at, for the objective of minimizing makespan 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 develop several dominance properties and a lower bound for the problem, and suggest a branch and bound algorithm implementing them. Also, In addition, heuristic algorithms that can be used for obtaining an initial upper bound in the B&B algorithm and for obtaining good solutions in a short time were developed. Computational experiments are performed on randomly generated test problems and results show that the suggested algorithm solves problems of a medium size in a reasonable amount of computation time. The proposed lower bound, the dominance properties, and the heuristics for upper bound are tested in B&B respectively, and the result showed that lower bound is effective to fathoming nodes and the dominance properties and heuristics also worked well. Also, it is showed that the CPU time required by this algorithm increases rapidly as the problem size increases. Therefore, the suggested B&B algorithm would be limited to solve large size problems. However, the employed heuristic algorithms can be effectively used in the B&B algorithm and can give good solutions for large problems within a few seconds.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.35 no.2
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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.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2018.05a
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• pp.41-42
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• 2018

Various methods that crash the project completion time have been studied. Line-of-Balance (LOB) is well accepted as a useful method that enables steady resource utilization without frequent hire-and-fire of resources for a project having repetitive units. Existing studies involved in LOB-CPM focuses on thesis such as resource leveling and optimization in construction scheduling community. However, crashing methods are not arrived at a full maturity in LOB scheduling, because no one handles steady resource utilization while keeping activity-relationships. This paper proposes a method that crashes project completion time by hybridizing concurrent engineering and LOB scheduling without using additional resources.

• 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.

• Management Science and Financial Engineering
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• v.5 no.2
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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.

• Journal of the military operations research society of Korea
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• v.33 no.1
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• pp.105-115
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• 2007

It is essential to give a fatal damage to the enemy force by using prompt and accurate fire in order to overcome the lack of artillery force. During the artillery fire operations, minimizing the firing time will secure the adapt ability in tactical operation. In this paper, we developed a mathematical model to schedule the artillery fire on the multiple targets to decrease total fire operation time. To design a program to describe a real firing situation, we consider many possible circumstances of changes such as commander's intention, firing constraints, target priority, and contingency plan to make a fire plan in an artillery unit. In order to work out the target sequencing problem, MIP is developed and the optimum solution is obtained by using ILOG OPL. If this analytical model is applied to a field artillery unit, it will improve the efficiency of the artillery fire force operations.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.1
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• pp.61-68
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• 2021

In the past, radars have been classified into fire control radars, detection radars, tracking radars, and image acquisition radars according to the characteristics of the mission. However, multi-function radars perform various tasks within a single system, such as target detection, tracking, identification friend or foe, jammer detection and response. Therefore, efficient resource management is essential to operate multi-function radars with limited resources. In particular, the target threat for tracking the detected target and the method of selecting the tracking cycle based on this is an important issue. If focus on tracking a threat target, Radar can't efficiently manage the targets detected in other areas, and if you focus on detection, tracking performance may decrease. Therefore, effective scheduling is essential. In this paper, we propose the TaP (Time and Priority) algorithm, which is a multi-functional radar scheduling scheme, and a software design method to construct it.