Recently, unmanned logistics delivery systems, such as UAV (Unmanned Aerial Vehicle, written as drone below) and autonomous robot delivery systems, have been implemented in many countries due to the rapid development of autonomous driving technology. The development of these new types of advanced unmanned logistics delivery systems is essential not only to become a leading logistics company but also to secure national competitiveness. In this paper, the application of the unmanned logistics delivery system was investigated in terms of market trends, overall technology level of last mile delivery drone and autonomous delivery robot. The direction of response to changes in the last mile delivery service market was checked through a comparison of the technological level between domestic companies that produce last mile devices and advanced foreign companies. As a result of this technology level analysis, the difference between domestic companies and advanced companies was shown using tables and figures to show their relative levels. The results of this analysis reflect the opinions of experts in the field of last-mile delivery technology. In addition, the technology level of unmanned logistics delivery systems for each country was analyzed based on the number of related technology patents. Lastly, insights for the technology level analysis of unmanned last mile delivery systems were proposed as a conclusion.

The concept of carsharing involves sharing a small number of reserved cars to be used individually by a larger number of people as required. This study examines the operating parameters of one-way carsharing systems in order to determine the appropriate operating conditions that minimizes the lost sales rate. Five operating parameters are tested in this study: the number of stations, the average number of vehicles per station, the rate of one-way trip, the average number of staffs per station, and the relocation policy. The performance of round-trip carsharing systems is also compared to that of one-way carsharing systems. A simulation model is developed and simulations are performed to determine the appropriate combination of operating parameter and levels. The simulation results show that the average number of vehicles per station is the most critical parameter. Other key findings obtained from this research are as follows. First, applying the appropriate relocation policy to one-way carsharing systems can allow more customers to rent vehicles than the traditional round-trip carsharing systems. Second, the appropriate relocation policy should be selected based on the average number of vehicles per station in order to minimize the lost sales rate. Third, the number of stations does not affect the lost sales rate. This study findings will provide tools to understand impact of the carsharing system parameters on the efficiency of the carsharing operations.

A cross docking operation involves multiple inbound trucks that deliver items from suppliers to a distribution center and multiple outbound trucks that ship items from the distribution center to customers. Based on customer demands, an inbound truck may have its items transferred to multiple outbound trucks. Similarly, an outbound truck can receive its consignments from multiple inbound trucks. The objective of this study is to find the best truck spotting sequence for both inbound and outbound trucks in order to minimize total operation time of the cross docking system under the condition that multiple visits to the dock by a truck to unload or load its consignments is allowed. The allocations of the items from inbound trucks to outbound trucks are determined simultaneously with the spotting sequences of both the inbound and outbound trucks.

Cross docking is a warehouse management concept in which items delivered to a distribution facility by inbound trucks are immediately sorted out and reorganized based on customer demands and are routed and loaded into outbound trucks for delivery to customers without actually being held in inventory in the distribution facility. In this research, the design of distribution facility for cross docking systems was studied. The objective of this research is to find the minimum number of receiving docks and shipping docks, respectively, in order to meet the daily demand of the distribution center. Two solution approaches are employed in modeling and solving the problem The first approach is mathematical modeling and the second approach is a simulation. The logic developed in the simulation model is expected to apply to the real world situation.

All of the city gas companies in Korea must employ the gas safety patrols by law. The gas safety patrols are responsible for the various tasks including daily gas pipeline patrol to prevent gas accidents. Since the size of jurisdiction varies among the city gas companies, it is very difficult to compare their efficiency for the operations of the safety patrol each other directly. The objective of this research is to develop the methodology to analyze and compare the efficiency of the safety patrol's operations among various city gas companies. Several factors that are related to the safety patrol's duty on the gas safety factors were identified and DEA(Data Envelopment Analysis) model for efficiency analysis was developed. Finally, the DEA model was applied to the collected data from six city gas companies. The less efficient city gas companies can benchmark the higher efficient city gas companies in order to improve the safety control systems.

A cross docking operation involves multiple trucks (known as inbound trucks) that deliver items from suppliers to a distribution center and multiple trucks (known as outbound trucks) that ship items from the distribution center to customers. Based on customer demands, an inbound truck may have its items transferred to multiple outbound trucks. Similarly, an outbound truck can receive its consignments from multiple inbound trucks. A unique characteristic of a cross docking system is the absence or prohibition of long term storage of items at the distribution center. Items delivered to the distribution center from suppliers are shipped to customers as soon as possible without being placed in storage in the distribution center. The objective of this paper is to develop the optimal operational strategy for finding the best truck docking sequence for both inbound and outbound trucks in order to minimize total operation time where a temporary storage area is not available in a cross docking system.

다양한 데이터 마이닝 기법들의 발전과 더불어, 속성 (Feature 또는 Attribute) 의 범위 (Dimension) 를 줄이기 위해 많은 요소 선택 방법이 개발되었다. 이는 확장성 (Scalability) 을 향상시킬 수 있고 학습 모델 (Learning Model)을 더욱 쉽게 해석할 수 있도록 한다. 이 논문에서는 네스티드 분할 (Nested Partition, 이하 NP) 을 이용한 새로운 최적화 기반 속성 선택 방법을 NP 기본 구조와 다양한 실험 문제의 수치적 결과들과 함께 제시하여 어떻게 NP의 최적화 구조가 속성 선택 과정에 기여를 하고 있는지 보여준다. 그리고 이 새로운 지능적인 분할 방법이 어떻게 매우 효율적인 분할을 수행하는지를 제시한다. 이 새로운 속성 선택 방법은 필터 (Filter) 방법과 래퍼 (Wrapper) 방법 두 가지로 구현될 수 있다. 사례 연구로서, B2B e-비즈니스 시스템에서 효과적으로 사용될 수 있는 추천 시스템(Recommender System) 을 제안하였다. 이 추천 시스템은 분류 기법 (Classification Rule) 과 제시된 NP 기반 요소 선택 방법을 사용하고 있다. 이 추천 시스템은 사용자의 인터넷 경매 참여를 추천하는데 사용되며, 이 때 제안된 요소 선택 앨고리듬은 추천 규칙들이 쉽게 이해될 수 있도록 모델을 간략화 하는데 사용된다.

  다양한 데이터 마이닝 기법들의 발전과 더불어, 속성 (Feature 또는 Attribute)의 범위 (Dimension)를 줄이기 위해 많은 요소 선택 방법이 개발되었다. 이는 확장성 (Scalability)을 향상시킬 수 있고 학습 모델 (Learning Model)을 더욱 쉽게 해석할 수 있도록 한다. 이 논문에서는 네스티드 분할 (Nested Partition, 이하 NP)을 이용한 새로운 최적화 기반 속성 선택 방법을 NP 기본 구조와 다양한

Both supply chain management and safety management contribute to strengthening a company's competitiveness. However, there is no previous research that considers supply chain management and safety management simultaneously The objective of this research is to study on application of safety management to supply chain. In this paper, the concept of supply chain safety management is defined. Based on the concept of supply chain safety management, supply chain safety management model is developed that consists of supply safety management, production safety management, storage safety management, and distribution safety management. In order to apply supply chain safety management, a methodology is developed that consists of four phases. Applying the supply chain safety management model, it is expected a company to lower cost as well as to raise customer satisfaction level.

크로스도킹은 물류센터의 운영 개념으로써 입고트럭에 의해 배달된 물품이 재고로써 보관됨이 없이 즉시 고객의 수요에 따라 재분류되어 출고트럭에 적재되어 고객에게 배달되는 프로세스로 구성된다. 본 연구에서는 임시보관 장소를 보유한 크로스도킹 시스템의 총 운영시간을 최소화하기 위한 입고 트럭과 출고 트럭의 일정계획 수립을 위한 수학적 모델을 개발하였다. 본 연구에서 개발한 모델의 적용으로 물류센터 내에서의 자재 취급 빈도 및 시간이 감소하여 제품 손상을 최소화