Effects-Based Operations (EBO) refers to a process for achieving strategic goals by focusing on effects rather than attrition-based destruction. For a successful implementation of EBO, identifying key nodes in an adversary network is crucial in the process of EBO. In this study, we suggest a network-based approach that combines network centrality and optimization to select the most influential nodes. First, we analyze the adversary’s network structure to identify the node influence using degree and betweenness centrality. Degree centrality refers to the extent of direct links of a node to other nodes, and betweenness centrality refers to the extent to which a node lies between the paths connecting other nodes of a network together. Based on the centrality results, we then suggest an optimization model in which we minimize the sum of the main effects of the adversary by identifying the most influential nodes under the dynamic nature of the adversary network structure. Our results show that key node identification based on our optimization model outperforms simple centrality-based node identification in terms of decreasing the entire network value. We expect that these results can provide insight not only to military field for selecting key targets, but also to other multidisciplinary areas in identifying key nodes when they are interacting to each other in a network.

Ship collision accidents not only endanger the safety of ships and personnel, but also may cause serious marine environmental pollution. To solve this problem, advanced technologies have been developed and applied in the field of intelligent ships in recent years. In this paper, a novel path planning algorithm is proposed based on particle swarm optimization (PSO) to construct a decision-making system for ship's autonomous collision avoidance using the process analysis which combines with the ship encounter situation and the decision-making method based on ship collision avoidance responsibility. This algorithm is designed to avoid both static and dynamic obstacles by judging the collision risk considering bad weather conditions by using BP neural network. When the two ships enter a certain distance, the optimal collision avoidance course and speed of the ship are obtained through the improved collision avoidance decision-making method. Finally, through MATLAB and Visual C++ platform simulations, the results show that the ship collision avoidance decision-making scheme can obtain reasonable optimal collision avoidance speed and course, which can ensure the safety of ship path planning and reduce energy consumption.

PURPOSES : The purpose of this study is to build an optimization model using the capacity and initial travel speed of the volume delay functions for network calibration performed in the traffic demand analysis process. METHODS : The optimization model contains an error term between the observed traffic volume and estimated traffic volume, based on the user equilibrium principle, and was constructed as a bi-level model by applying range constraints on capacity and travel time. In addition, we searched the split section to apply the method of adjusting the section instead of adjusting the single link. The optimization model is constructed by applying the warm-start method using the bush of the origin-based model so that parameter adjustment and traffic assignment are repeatedly executed within the model and the convergence of the model configured %RSSE. RESULTS : As a result of analysis using the toy network, the optimization model is that the observed traffic volume is estimated when there are no restrictions and, when the constraint conditions were set, the error with the observed traffic volume and error rate was significantly reduced. As a result of the comparative analysis of the trial-and-error methods, KTDB optimum values, and optimization models in empirical analysis using a large-scale network, the evaluation indexes (e.g., RMSE and %RMSE) were significantly improved by applying the optimization model. CONCLUSIONS : Based on the empirical analysis, the optimization model of this study can be applied to large-scale networks and it is expected that the efficiency and reliability of road network calibration will be improved by repeatedly performing parameter adjustment and traffic assignment within the model.

본 연구에서는 각기 다른 두 제조사의 AgNW를 활용하여 스핀코팅 속도, 열처리 온도 및 방법 그리고 PDMS코팅 속도에 따른 AgNW/PDMS composite공정 연구를 실시하였다. 실험결과 peel off 특성에 영향을 미치는 인자로 건조방식이 주요하게 작용하며 공정온도 또한 전극 특성에 영향을 주었다. 핫플레이트를 사용한 건조방식은 한방향 열전달로 인해 PDMS를 충분히 건조시키지 못하였지만 오븐 건조를 통해 그 결점을 보완할 수 있었다. 또한, PDMS 코팅속도가 증가함에 따라 스트레처블 특성이 향상되었고 GF는 0.03에서 0.07로 약 100정도 향상되었다.

This research carried out an analysis on input cost and leakage reduction effect by leakage reduction method, focusing on the project for establishing an optimal water pipe network management system in the Taebaek region, which has been executed annually since 2009. Based on the result, optimal cost-benefit analysis models for water distribution network rehabilitation project were developed using DEA(data envelopment analysis) and multiple regression analysis, which have been widely utilized for efficiency analysis in public and other projects. DEA and multiple regression analysis were carried out by applying 4 analytical methods involving different ratios and costs. The result showed that the models involving the analytical methods 2 and 4 were of low significance (which therefore were excluded), and only the models involving the analytical methods 1 and 3 were suitable. From the result it was judged that the leakage management method to be executed with the highest priority for the improvement of revenue water ratio was installation of pressure reduction valve, followed by replacement of water distribution pipe, replacement of water supply pipe, and then leakage detection and repair; and that the execution of leakage management methods in this order would be most economical. In addition, replacement of water meter was also shown to be necessary in case there were a large number of defective water meters.

Logistics cost of domestic company has been improved continuously and annually, it is still higher than other main comparative countries. So, in this study, as optimizing the logistic network of distribution, it was trying to find methods decreasing logistics cost and storage cost, which occupies 86% of logistics cost of companies. through the efficiency of transportation and delivery routing, it could be also possible to decrease the logistics cost. And, it is also checked to find the logistics cost could be decreased by 10% by optimizing the routes of transportation and delivery, improving the transportation mode, etc.

  This paper considers a topological optimization of a computer network design with a cost constraint. The objective is to find the topological layout of links, at maximal reliability, under the constraint that the network cost is less or equal than a giv

As the market of express delivery services expands rapidly, delivery service companies are exposed to severe competition. As a result of the surplus of delivery companies, they are struggling with remaining competitive at a reasonable price with appropriate level of customer satisfaction. To cope with competition pressures, a strategic alliance is suggested as an effective solution to the challenges faced by small and medium enterprises (SMEs) in express delivery services. Therefore, this study suggests a combined optimization and simulation approach to the reconfiguration of an express delivery service network for strategic alliance with respect to strategy partnership of closing/keeping service centers among companies involved and adjustments of their cutoff times. An illustrative numerical example is presented to demonstrate the practicality and efficiency of the approach.

크루즈 관광 산업은 모든 관광 산업 중 세계적으로 가장 빠르게 성장하고 있는 관광산업임에도 불구하고, 지금까지 합리적 크루즈 경영의사결정에 관한 학술적 연구가 매우 미진한 상황이다. 이 논문은 크루즈 경영에 관한 기초적인 전략적 의사결정이라고 할 수 있는 크루즈 운항일정계획을 다루고 있다. 이전에 개발된 한척의 크루즈선박에 관한 모형의 제한점을 극복하여, 여러 척의 크루즈선박으로 구성된 크루즈 선대를 일반적으로 다룰 수 있는 최적화 의사결정계획 모형을 개발하였다. 후보운항일정계획들 간의 복잡성을 체계화하기 위해 선박별 후보운항일정계획 네트워크를 제안하였으며, 후보운항일정계획 네트워크 전체를 통합하는 정수계획모형을 개발하였다. 공개된 크루즈 운항일정 자료들에 바탕을 둔 가상 사례를 활용하여 개발된 모형을 실험하였다.

본 연구에서는 주어진 수위관측망이 유역의 유출특성을 효과적으로 잡아낼 수 있느냐 하는 것에 초점을 맞추어 수위관측망을 평가하였다. 어떤 특수한 목적의 수위관측이나, 댐과 같은 구조물의 영향은 고려하지 알았으며, 단지 현존하는 수위관측소가 자연유량을 관측한다는 전제 하에 주어진 관측망의 최적화를 시도하였다. 본 연구는 남한강유역 내 총 31개의 수위관측소를 대상으로 수행하였으며, 수위관측망의 최적화에는 엔트로피의 개념을 이용하였다. 본 연구의 결과를 정리

우리나라 경북 동·남부지역은 지형조건과 원래 부족한 수자원으로 용수개발에 어려움을 겪는 지역이다. 이와 같은 물 문제를 완화시키기 위해 새로운 댐의 개발과 광역용수공급, 기존 용수공급 시스템의 조정, 오래된 댐의 개·증축 그리고 저류용댐의 건설 방안이 검토되었다. 새롭게 제시된 수자원 개발 대안의 평가는 수자원 시스템의 의사결정 도구로 많이 이용되고 있는 수학적 모형의 하나인 네트워크 최적화 모형을 이용하였다. 연구결과 용수공급 시스템이 2011년까지