In this study, Pleurotus ostreatus No.42 was cultured in glucose-peptone-yeast-wheat bran medium using a previously reported novel rotary draft tube bioreactor. Versatile peroxidase (VP), a lignin-degrading enzyme, was isolated from a pellet-type mycelium culture grown in the medium for seven days. The VP was purified by sequentially applying ultra-filtration, DEAESepharose CL-6B column, and Mono Q column. SDS-PAGE analysis revealed the molecular weight of VP to be 36.4 KDa with an isoelectric point of 3.65. The amino acid sequence was confirmed as VTCATGQTT. The purified VP was observed to possess the property of not only oxidizing Mn ions but also decomposing veratryl alcohol, a non-phenolic compound. The catalytic ability of VP is a subject for future research.

최근 노인 인구가 증가함에 따라, 이들의 삶의 질에 대한 사회적 관심도가 높아지고 있으며, 노인들의 건강하고 활기찬 노후를 고려하는 활동적 노후 및 고령친화도시의 개념이 주목받고 있다. 이러한 상황에서 많은 지자체는 노인들이 지역 사회에서 여생을 의미 있게 보낼 수 있도록 다양한 노인여가복지 서비스를 제공하기 위해 노력하고 있다. 그러나 실질적인 노인 수요에 부합하는 서비스 공급이 이루어지지 못하고 있으며, 지역별로 노인여가복지 서비스의 공간적 격차가 발생하고 있는 실정이다. 이는 노인여가복지 입지와 관련하여 체계적인 법적 기준이 부재하기 때문이다. 이에 본 연구는 서울시의 노인여가복지 시설에 대한 수요와 공급의 공간적 불일치성을 탐색하고, 공간 효율성과 형평성을 고려한 노인복지센터의 최적 입지 대안을 제시하고 있다. 연구 결과, 여러 입지 시나리오에 따라 서울시 노인복지센터의 공간적 접근성을 향상시킬 수 있는 다양한 최적 입지 대안들을 제시할 수 있었으며, 향후 노인복지 서비스 공급과 관련한 계획 및 정책에 있어 중요한 기초 자료로 활용될 수 있을 것으로 기대된다

Most of real-world decision-making processes are used to optimize problems with many objectives of conflicting. Since the betterment of some objectives requires the sacrifice of other objectives, different objectives may not be optimized simultaneously. Consequently, Pareto solution can be considered as candidates of a solution with respect to a multi-objective optimization (MOP). Such problem involves two main procedures: finding Pareto solutions and choosing one solution among them. So-called multi-objective genetic algorithms have been proved to be effective for finding many Pareto solutions. In this study, we suggest a fitness evaluation method based on the achievement level up to the target value to improve the solution search performance by the multi-objective genetic algorithm. Using numerical examples and benchmark problems, we compare the proposed method, which considers the achievement level, with conventional Pareto ranking methods. Based on the comparison, it is verified that the proposed method can generate a highly convergent and diverse solution set. Most of the existing multi-objective genetic algorithms mainly focus on finding solutions, however the ultimate aim of MOP is not to find the entire set of Pareto solutions, but to choose one solution among many obtained solutions. We further propose an interactive decision-making process based on a visualized trade-off analysis that incorporates the satisfaction of the decision maker. The findings of the study will serve as a reference to build a multi-objective decision-making support system.

This paper deals with a vehicle routing problem with resource repositioning (VRPRR) which is a variation of well-known vehicle routing problem with pickup and delivery (VRPPD). VRPRR in which static repositioning of public bikes is a representative case, can be defined as a multi-objective optimization problem aiming at minimizing both transportation cost and the amount of unmet demand. To obtain Pareto sets for the problem, famous multi-objective optimization algorithms such as Strength Pareto Evolutionary Algorithm 2 (SPEA2) can be applied. In addition, a linear combination of two objective functions with weights can be exploited to generate Pareto sets. By varying weight values in the combined single objective function, a set of solutions is created. Experiments accomplished with a standard benchmark problem sets show that Variable Neighborhood Search (VNS) applied to solve a number of single objective function outperforms SPEA2. All generated solutions from SPEA2 are completely dominated by a set of VNS solutions. It seems that local optimization technique inherent in VNS makes it possible to generate near optimal solutions for the single objective function. Also, it shows that trade-off between the number of solutions in Pareto set and the computation time should be considered to obtain good solutions effectively in case of linearly combined single objective function.

본 연구에서는 철골편심가새골조 시스템을 대상으로 다목적최적화기법을 통해 설계를 수행하고 그 결과를 분석하였다. 최적화 설 계를 위해 유전 알고리즘의 일종인 NSGA-II를 활용하였다. 여기서, 목적함수는 이율배반적 관계를 갖는 구조물량과 층간변위로 하여 최소화되고, 제약조건에는 구조기준에서 요구하는 내력비, 링크의 회전각 등을 포함하였다. 제약조건은 최적화 알고리즘 내에서 각 항목을 위반할수록 목적함수 값을 크게 증가시키는 벌금함수의 형태를 가지고 있다. 설계기준에서 EBF 시스템의 설계규정은 링크 부재만 항복이 허용되며 나머지 부재는 링크 항복 시 발생되는 부재력을 탄성상태에서 견디도록 의도한 역량설계법에 기초한다. 그러나 최적화를 통해 도출된 결과 중 일부는 구조기준의 설계조항은 만족하지만 특정층 링크에 소성변형이 집중되어 연약층을 형성함 으로써 기준에서 의도하는 역량설계의 원칙을 위배하는 결과가 나타났다. 이를 해결하기 위해 모든 링크의 전단 초과강도계수 중 최 대값이 최소값의 1.25배를 넘지 않도록 하는 제약식을 추가하였다. 새로운 제약식을 추가한 경우 모든 최적해는 설계기준과 역량설계의 원칙을 준수하는 것으로 나타났다. 모든 설계안에서 보 경간에 대한 링크의 길이비는 전단링크의 범주에 해당하는 10% ~ 14%였다. 전체적으로 설계안들은 링크의 초과강도 계수비가 가장 지배적인 제약으로 작용하였으며, 구조기준의 요구사항 중 층간변위와 내력비 등의 항목에서 허용치에 비해 매우 보수적으로 설계되었다.

In this study, a model to optimize residual chlorine concentrations in a water supply system was developed using a multi-objective genetic algorithm. Moreover, to quantify the effects of optimized residual chlorine concentration management and to consider customer service requirements, this study developed indices to quantify the spatial and temporal distributions of residual chlorine concentration. Based on the results, the most economical operational method to manage booster chlorination was derived, which would supply water that satisfies the service level required by consumers, as well as the cost-effectiveness and operation requirements relevant to the service providers. A simulation model was then created based on an actual water supply system (i.e., the Multi-regional Water Supply W in Korea). Simulated optimizations were successful, evidencing that it is possible to meet the residual chlorine concentration demanded by consumers at a low cost.

To make a satisfactory decision regarding project scheduling, a trade-off between the resource-related cost and project duration must be considered. A beneficial method for decision makers is to provide a number of alternative schedules of diverse project duration with minimum resource cost. In view of optimization, the alternative schedules are Pareto sets under multi-objective of project duration and resource cost. Assuming that resource cost is closely related to resource leveling, a heuristic algorithm for resource capacity reduction (HRCR) is developed in this study in order to generate the Pareto sets efficiently. The heuristic is based on the fact that resource leveling can be improved by systematically reducing the resource capacity. Once the reduced resource capacity is given, a schedule with minimum project duration can be obtained by solving a resource-constrained project scheduling problem. In HRCR, VNS (Variable Neighborhood Search) is implemented to solve the resource-constrained project scheduling problem. Extensive experiments to evaluate the HRCR performance are accomplished with standard benchmarking data sets, PSPLIB. Considering 5 resource leveling objective functions, it is shown that HRCR outperforms well-known multi-objective optimization algorithm, SPEA2 (Strength Pareto Evolutionary Algorithm-2), in generating dominant Pareto sets. The number of approximate Pareto optimal also can be extended by modifying weight parameter to reduce resource capacity in HRCR.

목적 : 본 연구는 다목적 암맹상자(multi-purpose blind box)를 개발하고 이의 효과성 검증을 통해 뇌졸중 환자의 감각과 시지각 기능향상을 위한 훈련도구로서의 역할을 제시하고자 하였다. 연구 방법 : 연구 대상자는 광역시 소재 병원에서 작업치료를 받고 있는 뇌졸중 환자 33명을 선정 하였다. 연구도구로서 본 연구에서 개발한 감각과 시지각 기능향상 훈련용 다목적 암맹상자를 활용하였으며, 평가 도구는 Semmes Weinstein Monofilament(SWM), Two-point Discrimination Test(TD), Modified Moberg Pickup Test(MPT), MVPT-3와 QUEST 2.0을 사용하였다. 대상자들은 무작위 할당을 통해 실험군과 대조군으로 분류한 후 초기평가를 실시하였으며 실험군에게는 다목적 암맹상자 훈련 프로그램을 1회당 30분간 주 3회를 시행하였다. 대조군은 전통적인 작업치료를 받도록 하였고 실험군과 대조군 모두 6주간 훈련 후 재평가를 실시하였다. 결과 : 다목적 암맹상자 훈련 전·후 실험군과 대조군의 SWM, TD, MPT 및 MVPT-3 점수 차이는 대조군보다 실험군에서 유의하게 더 높았다(p<.05). 또한 실험군에서는 다목적 암맹상자 훈련 시행 후 SWM과 TD 수치의 감소, MPT 시간의 감소 그리고 MVPT-3 점수는 향상됨을 보였다. 다목적 암맹상자 활용 후 사용성 평가는 모든 문항에서 보통 이상의 수준으로 대답하였다. 결론 : 본 연구결과 다목적 암맹상자를 이용한 훈련이 뇌졸중 환자의 감각과 시지각 기능에 긍정적인 영향을 미친다는 점을 알 수 있었고, 향후 훈련도구뿐만 아니라 평가도구로서도 활용할 수 있을 것을 기대한다.

According to the recent presentation by the Korean Maritime Safety Tribunal, about 70% of marine accident occurs from fishing vessel, and 90% of cause of entire marine accidents attributes to human error. As fishing vessels require basic operations, fishing operations, other additional operations and techniques such as fish handling, cultivating excellent marine officer to prevent marine accident and develop industry is very important. A fisheries training ship is still very difficult to satisfy the demand for diversity of fishery training and sense of realism of the industry. As the result of employment expectation by category of business survey targeting 266 marine industry high school graduates who hope to board fishing vessels for the last four years, tuna purse seine was the highest with 132 cadets (49.6%), followed by offshore large purse seine (65 cadets, 22.4%), and tuna long line (35 cadets, 13.2%). The Korea Institute of Maritime and Fisheries Technology (KIMFT) has replaced old jigging and fish pot fishery training ships and proceeded developing and building multi-purpose fisheries training ships considering the demand of industry and the promotion of employment; however, the basic fishing method was set for a tuna purse seine. As a result of seakeeping model test, it can conduct the satisfiable operation at sea state 5, and survive at sea state 8.

본 논문에서는 복합재 판 스프링의 설계 최적화를 위해 유전자 알고리즘을 사용한 적층 최적화 과정을 제시하였다. 다목적 소형 승합 자동차 판 스프링을 유한요소모델로 구성하여 초기 설계를 검증한 이후, 유전자 알고리즘을 통해 복합재료의 적층수와 적층각도를 최적화하는 과정을 기술하였다. 최적화 과정을 통해 판 스프링의 하중 감소과정, 반복수에 따라 강 구조의 해석 결과와 비교하였다. 더불어 유전자 알고리즘을 통해 최적화된 적층 시퀀스를 구조에 적용하여 구조의 건전성을 검증하기 위해 유한요소 모델로 구성하여 안전여유를 계산하였다. GA를 적용할 때, 복합재료 판 스프링의 적층 두께와 적층각을 획득하였으며, 이는 적절한 강도와 강성으로 최소 무게를 달성하는데 기여한다. 동일한 설계 매개 변수 및 최적화 조건에서 강철된 판 스프링을 복합재 판 스프링으로 교체하면 65.6%의 중량이 감소한다.

Direct spring loaded pressure relief valve(DSLPRV) is a safety valve to relax surge pressure of the pipeline system. DSLPRV is one of widely used safety valves for its simplicity and efficiency. However, instability of the DSLPRV can caused by various reasons such as insufficient valve volume, natural vibration of the spring, etc. In order to improve reliability of DSLPRV, proper selection of design factors of DSLPRV is important. In this study, methodology for selecting design factors for DSLPRV was proposed. Dynamics of the DSLPRV disk was integrated into conventional 1D surge pressure analysis. Multi-objective genetic algorithm was also used to search optimum design factors for DSLPRV.

The application of the theoretical model to real assembly lines has been one of the biggest challenges for researchers and industrial engineers. There should be some realistic approach to achieve the conflicting objectives on real systems. Therefore, in this paper, a model is developed to synchronize a real system (A discrete event simulation model) with a theoretical model (An optimization model). This synchronization will enable the realistic optimization of systems. A job assignment model of the assembly line is formulated for the evaluation of proposed realistic optimization to achieve multiple conflicting objectives. The objectives, fluctuation in cycle time, throughput, labor cost, energy cost, teamwork and deviation in the skill level of operators have been modeled mathematically. To solve the formulated mathematical model, a multi-objective simulation integrated hybrid genetic algorithm (MO-SHGA) is proposed. In MO-SHGA each individual in each population acts as an input scenario of simulation. Also, it is very difficult to assign weights to the objective function in the traditional multi-objective GA because of pareto fronts. Therefore, we have proposed a probabilistic based linearization and multi-objective to single objective conversion method at population evolution phase. The performance of MO-SHGA is evaluated with the standard multi-objective genetic algorithm (MO-GA) with both deterministic and stochastic data settings. A case study of the goalkeeping gloves assembly line is also presented as a numerical example which is solved using MO-SHGA and MO-GA. The proposed research is useful for the development of synchronized human based assembly lines for real time monitoring, optimization, and control.

The application of the theoretical model to real assembly lines has been one of the biggest challenges for researchers and industrial engineers. There should be some realistic approach to achieve the conflicting objectives on real systems. Therefore, in this paper, a model is developed to synchronize a real system (A simulation model) with a theoretical model (An optimization model). This synchronization will enable the realistic optimization of systems. A job assignment model of the assembly line is formulated for the evaluation of proposed realistic optimization with multiple objectives. The objectives, fluctuation in cycle time, throughput, labor cost, energy cost, teamwork and deviation in the skill level of operators have been modeled mathematically. To solve the formulated mathematical model, a multi-objective simulation integrated hybrid genetic algorithm (MO-SHGA) is proposed. The performance of MO-SHGA is evaluated with the standard multi-objective genetic algorithm (MO-GA) with both deterministic and stochastic data settings. A case study of the goalkeeping gloves assembly line is also presented as a numerical example which is solved using MO-SHGA and MO-GA.