When considering military operations that require rapid response time, forward supply operation of various type of ammunition is essential. Also, t is necessary to supply ammunition in a timely manner before an ammunition shortage situation occurs. In this study, we propose a mathematical model for allocation of ammunition to ammunition storehouse at the Ammunition Supply Post (ASP). The model has several objectives. First, it ensures that the frequent used ammunition is stored in a distributed manner at a high workability ammunition storehouses. Second, infrequent used ammunition is required to be stored intensively at a single storehouse as much as possible. Third, capacity of the storehouse and compatible storage restriction required to be obeyed. Lastly, criticality of ammunition should be considered to ensure safety distance. We propose an algorithm to find the pareto-based optimal solution using the mathematical model in a reasonable computation time. The computational results show that the suggested model and algorithm can solve the real operational scale of the allocation problem.

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.

A missile defense system is composed of radars detecting incoming missiles aiming at defense assets, command control units making the decisions on weapon target assignment, and artillery batteries firing of defensive weapons to the incoming missiles. Although, the technology behind the development of radars and weapons is very important, effective assignment of the weapons against missile threats is much more crucial. When incoming missile targets toward valuable assets in the defense area are detected, the asset-based weapon target assignment model addresses the issue of weapon assignment to these missiles so as to maximize the total value of surviving assets threatened by them. In this paper, we present a model for an asset-based weapon assignment problem with shoot-look-shoot engagement policy and fixed set-up time between each anti-missile launch from each defense unit. Then, we show detailed linear approximation process for nonlinear portions of the model and propose final linear approximation model. After that, the proposed model is applied to several ballistic missile defense scenarios. In each defense scenario, the number of incoming missiles, the speed and the position of each missile, the number of defense artillery battery, the number of anti-missile in each artillery battery, single shot kill probability of each weapon to each target, value of assets, the air defense coverage are given. After running lpSolveAPI package of R language with the given data in each scenario in a personal computer, we summarize its weapon target assignment results specified with launch order time for each artillery battery. We also show computer processing time to get the result for each scenario.

셀룰러 시스템에서의 OFDM(Orthogonal Frequency Division Multiplexing)기술의 사용은 단일 반송파 기술과 비교하였을 때 뛰어난 주파수 효율과 광대역 구현 용이성을 가지고 있으나 차세대 이동통신 시스템과 같은 셀룰러 환경 하에서 사용될 시에는 여러 가지 극복해야 할 문제점을 가지고 있다. 그 중에서 해결해야 할 대표적인 문제점은 셀 간 간섭문제이다. 대표적인 채널 할당 기법은 Siemens의 주파수 할당 기법과 ETRI의 주파수 할당 기법이 있는데 Siemens 기법은 간섭문제가 적지만 시스템 효율이 떨어지고, ETRI 기법은 시스템 효율이 증가하나 간섭문제가 Siemens 기법에 비하여 간섭문제와 시스템 복잡도가 커진다는 단점을 가지고 있다. 이러한 단점을 보완하기 위해 본 연구는 실제 특정 지역에서의 사용자 분포를 고려하여 위 두 기법의 특성을 적절히 혼합한 Dynamic 주파수 할당 기법을 적용하여 동일한 조건 하에서 간섭문제를 최소화하면서도 시스템 효율을 높여 사용자 만족을 최대로 할 수 있도록 하고자 한다. 이를 위해 단말의 수를 랜덤으로 분포시켜 해당 셀 내의 사용자 수의 분포에 따라 가변적인 주파수 할당 기법을 적용하고 이를 모의실험을 통해 확인하도록 한다.

This paper proposes a hierarchical approach to the machine loading problem when the workload and tool magazine capacity of each machine are restrained. This heuristic approach reduces the maximum workload of the machines by partially grouping them. This research deals with situations where different groups of machines performing the same operation require different processing times. This work proposes a solution that is comprised of two phases. In first phase, demand is divided into batches and then operations are allocated. In Phase II, the processing time of the operation is different for each machine group, which is composed of the same identical machines; however, these machines can perform different sets of operations if tooled differently. In partial grouping, each machine is tooled differently, but they can assist one another in processing each individual operation.

In designing and operating cellular networks, it is assumed that the area of coverage is geographically divided into hexagonal cells. Among these cells, a certain number of cells are chosen to install switches that serve as relays for communications between any pair of cells. Then, each cell is assigned to a switch to complete the cellular network. This decision regarding assignment of cells to switches is known as a CSA (Cell-to-Switch Assignment) problem. Since this problem is so-called NP hard problem, many researches have proposed heuristic-based algorithms to provide near-optimal solutions with a reasonable computation time. Considering these characteristics of the CSA problem, this work develops a genetic algorithm and a local search algorithm. Throu호out a number of experiments, the performance of the proposed algorithms are evaluated, and compared with existing heuristic method

이 논문은 공공 컨테이너 터미널에서 직면하는 선석할당 계획문제를 다루고 있다. 선석할당 계획문제의 주된 논점은 ETA가 주어진 컨데이너 선박들을 어떻게 선석에 할당할 것인가를 결정하는 것이다. 선석할당 계획문제의 세 가지 최적화 모형들은 집합 문제 유형으로 정식화시켜 제시하였다. 또한, 제안된 최적화 모형의 의사결정 변수를 생성하기 위한 경험론적 알고리듬은 선박의 대기시간과 선석 점유율을 사용하여 고안하였다. 계산 실험은 실제 공공 컨데이너 터미널의 데이터로 수행하였으며, 그 결과들은 제안된 최적화 모형들과 경험론적 알고리듬들이 공공 컨테이너 터미널의 선석할당 계획문제에 대하여 유용하게 적용될 수 있음을 제시하고 있다.