PURPOSES : This study is to analyze the reduction effect on road pavement damage from the installation of weigh-in-motion systems used for overloaded vehicle enforcement, from the perspective of traffic assignment. METHODS : Fixed-demand multi-class traffic assignment was conducted by VISUM, a macroscopic traffic simulation software. We considered three vehicle classes and calculated the traffic load for each road link using the ESAL(Equivalent Single Wheel Load) factor, as proposed by ASHTTO(American Association of State Highway and Transportation Officials). We set up scenarios with weigh-in-motion installations in certain sections and observed how the traffic load changed before and after the installation of weigh-in-motion for each scenario. RESULTS : Three main trends were observed. Firstly, at points where weigh-in-motion systems were installed, traffic load significantly decreased even with the influx of cars and trucks following the restriction of overloaded trucks, highlighting the significant influence of overweight vehicles on the traffic load. Secondly, even when overweight vehicles detoured, there was no significant change in the overall network's traffic load. Lastly, the detour of overweight vehicles led to an increase in the total driving distance and time for all vehicles. CONCLUSIONS : Installing weigh-in-motion systems in sections with a lower structure number, which indicates thinner road pavement, can prevent damage in those specific areas without affecting the entire road network.

During wartime, the operation of engineering equipment plays a pivotal role in bolstering the combat prowess of military units. To fully harness this combat potential, it is imperative to provide efficient support precisely when and where it is needed most. While previous research has predominantly focused on optimizing equipment combinations to expedite individual mission performance, our model considers routing challenges encompassing multiple missions and temporal constraints. We implement a comprehensive analysis of potential wartime missions and developed a routing model for the operation of engineering equipment that takes into account multiple missions and their respective time windows of required start and completion time. Our approach focused on two primary objectives: maximizing overall capability and minimizing mission duration, all while adhering to a diverse set of constraints, including mission requirements, equipment availability, geographical locations, and time constraints.

In the (3,3) close combat model based on the Lanchester Square Law, this study proposes a plan to optimally allocate residual combat power after the battle to other battlefields. As soon as the two camps of three units can grasp each other's information and predict the battle pattern immediately after the battle began, the Time Zero Allocation of Force (TZAF) scenario was used to initially allocate combat power to readjust the combat model. It reflects travel time, which is a "field friction" in which physical distance exists from battlefields that support combat power to battlefields that are supported. By developing existing studies that try to examine the effect of travel time on the battlefield through the combat model, this study forms a (3,3) combat model, which is a large number of minimum units. In order to achieve the combat purpose, the principle of optimal combat force operation is presented by examining the aspect that support combat power is allocated to the two battlefields and the consequent battle results. Through this, various scenarios were set in consideration of the travel time and the situation of the units, and differentiated results were obtained. Although the most traditional, it can be used as the basic logic of the training or the commander's decision-making system using the actual war game model.

During wartime, the operation of engineering equipment plays a pivotal role in bolstering the combat prowess of military units. To fully harness this combat potential, it is imperative to provide efficient support precisely when and where it is needed most. While previous research has predominantly focused on optimizing equipment combinations to expedite individual mission performance, our model considers routing challenges encompassing multiple missions and temporal constraints. We implement a comprehensive analysis of potential wartime missions and developed a routing model for the operation of engineering equipment that takes into account multiple missions and their respective time windows. Our approach centered on two primary objectives: maximizing overall capability and minimizing mission duration, all while adhering to a diverse set of constraints, including mission requirements, equipment availability, geographical locations, and time constraints.

본 연구는 중국의 11개 4F급 공항을 대상으로 변이할당분석을 통해 공항의 경쟁 력을 비교한다. 분석기간은 2001년-2021년으로 설정하고 2001년-2007년, 2008년-201 8년 그리고 2019년-2021년 세 구간을 설정하고 있다. 변이효과를 권역별로 보면 화 북지역의 공항 경쟁력은 감소하고 있으며, 화동지역, 화남지역과 화중지역의 공항 경 쟁력은 모두 상승하고 있다. 반대로 서북지역과 서남지역은 공항 경쟁력이 감소하고 있다. 할당효과를 보면 북경수도국제공항과 상해포동국제공항, 광주백운국제공항, 그 리고 심천보안국제공항의 할당효과가 가장 크다. 그리고 권역별로 절대적 성장치와 할당효과의 분석결과를 종합해 보면 화동지역, 화남지역 그리고 화중지역의 공항 경 쟁력이 상대적으로 높으며, 화북지역과 서북지역 그리고 서남지역의 공항 경쟁력은 상대적으로 낮다고 해석할 수 있다.

North Korea continues to upgrade and display its long-range rocket launchers to emphasize its military strength. Recently Republic of Korea kicked off the development of anti-artillery interception system similar to Israel’s “Iron Dome”, designed to protect against North Korea’s arsenal of long-range rockets. The system may not work smoothly without the function assigning interceptors to incoming various-caliber artillery rockets. We view the assignment task as a dynamic weapon target assignment (DWTA) problem. DWTA is a multistage decision process in which decision in a stage affects decision processes and its results in the subsequent stages. We represent the DWTA problem as a Markov decision process (MDP). Distance from Seoul to North Korea’s multiple rocket launchers positioned near the border, limits the processing time of the model solver within only a few second. It is impossible to compute the exact optimal solution within the allowed time interval due to the curse of dimensionality inherently in MDP model of practical DWTA problem. We apply two reinforcement-based algorithms to get the approximate solution of the MDP model within the time limit. To check the quality of the approximate solution, we adopt Shoot-Shoot-Look(SSL) policy as a baseline. Simulation results showed that both algorithms provide better solution than the solution from the baseline strategy.

In weapon assignment studies to defend against threats such as ballistic missiles and long range artillery, threat assessment was partially lacking in analysis of various threat attributes, and considering the threat characteristics of warheads, which are difficult to judge in the early flight stages, it is very important to apply more reliable optimal solutions than approximate solution using LP model, Meta heuristics Genetic Algorithm, Tabu search and Particle swarm optimization etc. Our studies suggest Generic Rule based threat evaluation and weapon assignment algorithm in the basis of various attributes of threats. First job of studies analyzes information on Various attributes such as the type of target, Flight trajectory and flight time, range and intercept altitude of the intercept system, etc. Second job of studies propose Rule based threat evaluation and weapon assignment algorithm were applied to obtain a more reliable solution by reflection the importance of the interception system. It analyzes ballistic missiles and long-range artillery was assigned to multiple intercept system by real time threat assessment reflecting various threat information. The results of this study are provided reliable solution for Weapon Assignment problem as well as considered to be applicable to establishing a missile and long range artillery defense system.

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.

The cooperative game theory consists of a set of players and utility function that has positive values for a subset of players, called coalition, in the game. The purpose of cost allocation method is to allocate the relevant cost among game players in a fair and rational way. Therefore, cost allocation method based on cooperative game theory has been applied in many areas for fair and reasonable cost allocation. On the other hand, the desirable characteristics of the cost allocation method are Pareto optimality, rationality, and marginality. Pareto optimality means that costs are entirely paid by participating players. Rationality means that by joining the grand coalition, players do not pay more than they would if they chose to be part of any smaller coalition of players. Marginality means that players are charged at least enough to cover their marginal costs. If these characteristics are all met, the solution of cost allocation method exists in the core. In this study, proportional method is applied to EOQ inventory game and EPQ inventory game with shortage. Proportional method is a method that allocates costs proportionally to a certain allocator. This method has been applied to a variety of problems because of its convenience and simple calculations. However, depending on what the allocator is used for, the proportional method has a weakness that its solution may not exist in the core. Three allocators such as demand, marginal cost, and cost are considered. We prove that the solution of the proportional method to demand and the proportional method to marginal cost for EOQ game and EPQ game with shortage is in the core. The counterexample also shows that the solution of the proportional method to cost does not exist in the core.

In the field of optimization, many studies have been performed on various types of Vehicle Routing Problem (VRP) for a long time. A variety of models have been derived to extend the basic VRP model, to consider multiple truck terminal, multiple pickup and delivery, and time windows characteristics. A lot of research has been performed to find better solutions in a reasonable time for these models with heuristic approaches. In this paper, by considering realtime traffic characteristics in Map Navigation environment, we proposed a method to manage realistic optimal path allocation for the logistics trucks and cargoes, which are dispersed, in order to realize the realistic cargo mixing allowance and time constraint enforcement which were required as the most important points for an online logistics brokerage service company. Then we developed a prototype system that can support above functionality together with delivery status monitoring on Map Navigation environment. First, through Map Navigation system, we derived information such as navigation-based travel time required for logistics allocation scheduling based on multiple terminal multiple pickup and delivery models with time constraints. Especially, the travel time can be actually obtained by using the Map Navigation system by reflecting the road situation and traffic. Second, we made a mathematical model for optimal path allocation using the derived information, and solved it using an optimization solver. Third, we constructed the prototype system to provide the proposed method together with realtime logistics monitoring by arranging the allocation results in the Map Navigation environment.