Efficiently detecting the nearest navigational dangers in Electronic Chart Display and Information Systems (ECDIS) remains pivotal for maritime safety. However, the software implementation of ADMAR(Automatic Distance measurement and Ranging) functionality faced challenges, necessitating extensive computations across ENC cells and impacting real-time performance. To address this, we present a novel method employing dynamic programming. Our proposed algorithm strategically organizes nodes into a tree structure, optimizing the search process towards nodes likely to contain navigational hazards. Implementation of this method resulted in a notable sevenfold reduction in computation time compared to the conventional Brute Force approach. Our study established a direct correlation between the ADMAR functionality and node count, achieving error margins deemed acceptable for practical navigation scenarios. Despite this theoretical progress, minor errors in results prompt further refinement. Consequently, future iterations will explore varying values for N, considering hierarchy and cell sizes to enhance algorithmic precision. This research signifies a potential advancement in optimizing navigational danger detection within ECDIS, offering a promising avenue for improved efficiency. By introducing a dynamic programming-based approach, we have streamlined the detection process while acknowledging the scope for algorithmic refinement in subsequent studies. Our findings underline the feasibility of employing dynamic programming to enhance navigational danger detection, emphasizing its potential in ensuring maritime safety. This work lays a foundation for future research endeavors, aiming to fine-tune algorithms and advance navigational safety measures in ECDIS.

This paper studied the problem of determining the optimal inventory level to meet the customer service target level in a situation where the customer demand for each branch of a nationwide retailer is uncertain. To this end, ISR (In-Stock Ratio) was defined as a key management indicator (KPI) that can be used from the perspective of a nationwide retailer such as Samsung, LG, or Apple that sells goods at branches nationwide. An optimization model was established to allow the retailer to minimize the total amount of inventory held at each branch while meeting the customer service target level defined as the average ISR. This paper proves that there is always an optimal solution in the model and expresses the optimal solution in a generalized form using the Karush-Kuhn-Tucker condition regardless of the shape of the probability distribution of customer demand. In addition, this paper studied the case where customer demand follows a specific probability distribution such as a normal distribution, and an expression representing the optimal inventory level for this case was derived.

Korea Radioactive Waste Agency (KORAD), regulatory body and civic groups are calling for an infrastructure system that can more systematically and safely manage data on the results of radioactive waste sampling and nuclide analysis in accordance with radioactive waste disposal standards. To solve this problem, a study has been conducted on the analysis of the nuclide pattern of radioactive waste on the nuclide data contained in low-and intermediate-level radioactive waste. This paper will explain the optimal repackaged algorithm for reducing radioactive waste based on previous research results. The optimal repackaged algorithm for radioactive waste reduction is comprised based on nuclide pattern association indicators, classification by nuclide level of small-packaged waste, and nuclide concentration. Optimization simulation is carried out in the order of deriving nuclide concentration by small-packaged, normalizing drum minimization as a function of purpose, normalizing constraints, and optimization. Two scenarios were applied to the simulation. In Scenario 1 (generating facilities and repackaged by medium classification without optimization), it was assumed that there are 886 low-level drums and 52 very low-level drums. In Scenario 2 (generating facilities and repackaged by medium classification with optimization), 708 and 230 drums were assigned to the low-level and very low-level drums, respectively. As a result of the simulation, when repackaged in consideration of the nuclide concentration and constraints according to the generating facility cluster & middle classification by small package (Scenario 2) the low-level drum had the effect of reducing 178 drums from the baseline value of 886 drums to 708 drums. It was found that the reduced packages were moved to the very low-level drum. The system that manages the full life-cycle of radioactive waste can be operated effectively only when the function of predicting or tracking the occurrence of radioactive waste drums from the source of radioactive waste to the disposal site is secured. If the main factors affecting the concentration and pattern of nuclides are systematically managed through these systems, the system will be used as a useful tool for policy decisions that can prevent human error and drastically reduce the generation of disposable drums.

This study studied a system that can redesign the production site layout and respond with dynamic simulation through fabric production process innovation for smart factory promotion and digital-oriented decision making of the production process. We propose to reflect the required throughput and throughput per unit facility of fabric production process as probability distribution, and to construct data-driven metabolism such as data collection, data conversion processing, data rake generation, production site monitoring and simulation utilization. In this study, we demonstrate digital-centric field decision smartization through architectural design for the smartization of fabric production plants and dynamic simulations that reflect it.

신재생 에너지 자원중 풍력발전은 비약적인 기술 발전과 시장 규모가 급속하게 성장하고 있다. 최근 육상풍력발전단지의 공간적 한계, 환경 문제 등으로 인하여 설치 공간이 해상으로 이동되었고, 더욱 풍부한 풍황 조건을 가진 깊은 수심에 설치되는 부유식 해상 풍력단지의 개발이 활발하게 진행되고 있다. 해상교통관점에서 해상풍력단지의 최적위치 선정은 선박과 풍력기들의 간섭을 최소화 하고 사고 확률이 적은 곳이며, 선박 밀집도가 낮은 해역이 최적위치로 선정된다. 본 연구에서는 유전 알고리즘 기반의 계절별 1주일 기간 선박자동식별장치 데이터를 유전자 및 염색체로 구성하였다. 80개의 유전자로 구성하고 유전 알고리즘의 적합도 평가를 거쳐 부유식 해상 풍력단지의 계절별 최적위치를 선정하였다. 더 나아가 계절별 최적위치 점수를 합산하여 최종 최적위치를 선정하였다. 분석 해역에서 최적위치는 11개로 나타났으며, 해상교통관점에서 유전 알고리즘을 통한 최적위치 선정이 적용 가능함을 확인하였다.

이 논문에서는 다중 재난을 고려한 복합 구조제어 시스템의 최적 설계방법을 제시한다. 한 가지 유형의 위험에 대해 하나의 시스템이 설계되는 전형적인 구조제어 시스템과는 달리, 구조물의 지진 및 바람에 의한 진동응답을 저감하기 위해 능동 및 수동제어 시스템에 대한 동시 최적 설계방법을 제안하였다. 수치 예로서, 30층 빌딩 구조물에 설치된 30개의 점성 댐퍼와 복합형 질량 감쇠기에 대한 최적 설계문제를 보였다. 최적화 문제를 풀기 위해 자체적응 화음탐색(harmony search, HS)알 고리즘을 채택하였다. 화음탐색 알고리즘은 사람이 연주하는 악기의 튜닝 과정을 모방한 전역 최적화를 위한 메타 휴리스틱 진화 연산방법의 하나이다. 또한 전역 탐색 및 빠른 수렴을 위해 자가적응적이고 동적인 매개변수 조정 알고리즘을 도입하였다. 최적화 설계 결과, 능동 및 수동 시스템이 독립적으로 최적화된 표준적인 복합제어 시스템에 비해 제안한 동시 최적제어 시스템의 성능과 효율성이 우수함을 보였다.

본 연구에서는 철근콘크리트 건물에 대한 유전자 알고리즘 기반의 최적구조설계기법을 제시하고자 한다. 목적함수는 구조 물의 비용과 이산화탄소 배출량을 동시에 각각 최소화하는 것이다. 비용 및 인산화탄소 배출량은 구조설계안에서 얻을 수 있는 단면치수, 부재길이, 재료강도, 철근량 등과 같은 설계정보를 통해 계산한다. 즉, 구조물의 물량을 기초로 하여 비용과 이산화탄소 배출량을 평가한다. 재료의 운반, 시공 및 건물 운영 단계에서 발생하는 비용 및 이산화탄소 배출량은 본 연구에 서 제외한다. 제약조건은 철근콘크리트 건물을 구성하는 기둥과 보 부재의 강도조건과 층간변위조건이 고려된다. 제약조건 을 평가하기 위해 OpenSees를 활용한 선형정적해석이 수행된다. 제약조건을 만족시키면서 목적함수에 대해 최소의 값을 제 시하는 설계안을 찾기 위해 유전자 알고리즘이 사용된다. 제시한 알고리즘의 적용성을 검증하기 위해 4층 철근콘크리트 모 멘트 골조 예제에 제시하는 기법을 적용하여 검증한다.

본 연구에서는 철골모멘트골조의 보-힌지 붕괴모드를 유도하는 최적 내진설계기법을 제안한다. 이는 유전자알고리즘을 사용하며, 기둥의 소성힌지 발생을 억제하는 제약조건을 설정하여 보-힌지 붕괴모드를 유도한다. 제안하는 기법은 구조물량를 최소화하고 에너지소산능력을 최대화하는 목적함수를 사용한다. 제안하는 기법은 9층 철골모멘트골조 예제 적용을 통해 검증한다. 예제 적용을 통해 철골모멘트골조의 보-힌지 붕괴모드를 유도하기 위해 요구되는 기둥-보 강도비를 평가한다. 패널존에 대한 3가지 모델링 기법을 각각 적용하여 모델링 조건에 따른 휨강도비 영향이 추가적으로 검토된다.

This paper is concerned with an experimental research to control of random vibration caused by external loads specially in cable-stayed bridges which tend to be structurally flexible. For the vibration control, we produced a model structure modelled on Seohae Grand Bridge, and we designed a shear type MR damper. On the center of its middle span, we placed a shear type MR damper which was to control its vibration and also acquire its structural responses such as displacement and acceleration at the same site. The experiments concerning controlling vibration were performed according to a variety of theories including un-control, passive on/off control, and clipped-optimal control. Its control performance was evaluated in terms of the absolute maximum displacements, RMS displacements, the absolute maximum accelerations, RMS accelerations, and the total power required to control the bridge which differ from each different experiment method. Among all the methods applied in this paper, clipped-optimal control method turned out to be the most effective to reduces of displacements, accelerations, and external power. Finally, It is proven that the clipped-optimal control method was effective and useful in the vibration control employing a semi-active devices such MR damper.

Optimal design of the water supply pipe network aims to minimize construction cost while satisfying the required hydraulic constraints such as the minimum and maximum pressures, and velocity. Since considering one single design factor (i.e., cost) is very vulnerable for including future conditions and cannot satisfy operator’s needs, various design factors should be considered. Hence, this study presents three kinds of design factors (i.e., minimizing construction cost, maximizing reliability, and surplus head) to perform multi-objective optimization design. Harmony Search (HS) Algorithm is used as an optimization technique. As well-known benchmark networks, Hanoi network and Gyeonggi-do P city real world network are used to verify the applicability of the proposed model. In addition, the proposed multi-objective model is also applied to a real water distribution networks and the optimization results were statistically analyzed. The results of the optimal design for the benchmark and real networks indicated much better performance compared to those of existing designs and the other approach (i.e., Genetic Algorithm) in terms of cost and reliability, cost, and surplus head. As a result, this study is expected to contribute for the efficient design of water distribution networks.

PURPOSES : The Toll Collection System (TCS) operated by the Korea Expressway Corporation provides accurate traffic counts between tollgates within the expressway network under the closed-type toll collection system. However, although origin-destination (OD) matrices for a travel demand model can be constructed using these traffic counts, these matrices cannot be directly applied because it is technically difficult to determine appropriate passenger car equivalent (PCE) values for the vehicle types used in TCS. Therefore, this study was initiated to systematically determine the appropriate PCE values of TCS vehicle types for the travel demand model. METHODS: To search for the appropriate PCE values of TCS vehicle types, a traffic demand model based on TCS-based OD matrices and the expressway network was developed. Using the traffic demand model and a genetic algorithm, the appropriate PCE values were optimized through an approach that minimizes errors between actual link counts and estimated link volumes. RESULTS : As a result of the optimization, the optimal PCE values of TCS vehicle types 1 and 5 were determined to be 1 and 3.7, respectively. Those of TCS vehicle types 2 through 4 are found in the manual for the preliminary feasibility study. CONCLUSIONS: Based on the given vehicle delay functions and network properties (i.e., speeds and capacities), the travel demand model with the optimized PCE values produced a MAPE value of 37.7%, RMSE value of 17124.14, and correlation coefficient of 0.9506. Conclusively, the optimized PCE values were revealed to produce estimates of expressway link volumes sufficiently close to actual link counts.

Recently, a concept of damped outrigger system has been proposed for tall buildings. Structural characteristics and design method of this system were not sufficiently investigated to date. In this study, control performance of damped outrigger system for building structures subjected to seismic excitations has been investigated. And optimal design method of damped outrigger system has been proposed using multi-objective genetic algorithm. To this end, a simplified numerical model of damped outrigger system has been developed. State-space equation formulation proposed in previous research was used to make a numerical model. Multi-objective genetic algorithms has been employed for optimal design of the stiffness and damping parameters of the outrigger damper. Based on numerical analyses, it has been shown that the damped outrigger system control dynamic responses of the tall buildings subjected to earthquake excitations in comparison with a traditional outrigger system.

본 논문은 전국적인 소매업체의 각 지점별 고객 수요가 불확실한 상황에서 고객 서비스 목표 수준을 충족하는 최적 재고 수준을 결정하는 문제에 대해 연구하였다. 이를 위해 전국에 분포한 지점에서 물품을 판매하는 베스트바이, 월마트, 혹은 시어스와 같은 전국적인 소매업체 관점에서 사용할 수 있는 핵심 관리 지표(KPI)로서 ISR(In-Stock Ratio)를 정의하였으며, 전국적인 소매업체가 평균 ISR로 정의되는 고객 서비스 목표 수준을 충족하면서 각 지

수리가능 제품은 가격 비싸고 중요성이 크면서 새 제품을 구매하기 어려운 부품을 의미하며, 항공기 또는 선박의 엔진 등을 들 수 있다. 수리가능 제품에 대하여 고장이 발생할 경우 가용성을 유지하기 위하여 즉지 교체하여야 하고, 교체된 부품은 수리에 들어가야 한다. 이러한 문제에 대한 통제 시스템은 시스템의 효율성을 결정하는 중요한 요소이기 때문에, 다양한 시스템 구성에 대하여 많은 연구가 이루어져 왔다. 본 연구에서는 우선 중앙 수리기지와 여러 지역 수리

Reliability has been considered as a one of the major design measures in various industrial and military systems. The main objective is to suggest a mathematical programming model and a hybrid parallel genetic algorithm(HPGA) for the problem that determin

The large-scale disasters occur to unexpected accidents such as natural disasters(earthquake, typhoon, tsunami, etc.), and human-caused accidents(fire, collapse, terror etc.). Rescue teams perform rescue activities to save many lives in large-scale disaster area. The main purpose of this study is to compose a optimal routing planning for rescue of multiple victims in disaster area. A realistic routing planning with rescue limit time which considers rehabilitation and reconstruction will be suggested in this study. A mathematical programming model and a hybrid genetic algorithm will be suggested to minimize the total spending time. By comparing the result, the suggested algorithm gives a better solution than existing algorithms.

This paper considers how the optimal export level is influenced by export risk, the degree of risk-averseness for exporting firms, and those firms' cost structure. In addition, export insurance is incorporated into some simple theoretical model to analyze