• 한국군사과학기술학회지
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• 제13권6호
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• pp.1091-1098
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• 2010

Victory and defeat of the war depends on follow-on logistics support. The spending time of follow-on logistics support at combat area is greatly influenced by the degree of combat intensity. The main purpose of this study is to compose a optimal supply route for operational sustainability of combat unit at combat area using transport vehicles. This study suggests a composition of optimal supply route for follow-on logistics support which considers the degree of combat intensity. A mathematical programming model and a genetic algorithm suggest to minimize the total spending time of follow-on logistics support. The suggested mathematical programming model is verified by using CPLEX 11.1. This study computes supply route, total spending time, total travel distance, and the number of transport vehicle.

• International journal of advanced smart convergence
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• 제12권3호
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• pp.221-232
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• 2023

Recently, due to the expansion of the logistics industry, demand for logistics automation equipment is increasing. The modern logistics industry is a high-tech industry that combines various technologies. In general, as various technologies are grafted, the complexity of the system increases, and the occurrence rate of defects and failures also increases. As such, it is time for a predictive maintenance model specialized for logistics automation equipment. In this paper, in order to secure the operational reliability of the ICT/Cold-Chain Unmanned Storage, a predictive maintenance system was implemented based on the LSTM model. In this paper, a server for data management, such as collection and monitoring, and an analysis server that notifies the monitoring server through data-based failure and defect analysis are separately distinguished. The predictive maintenance platform presented in this paper works by collecting data and receiving data based on RabbitMQ, loading data in an InMemory method using Redis, and managing snapshot data DB in real time. The predictive maintenance platform can contribute to securing reliability by identifying potential failures and defects that may occur in the operation of the ICT/Cold-Chain Unmanned Storage in the future.

• 대한산업공학회지
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• 제35권1호
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• pp.1-14
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• 2009

The efficiency of transportation requests fulfillment can be increased through extending the problem of vehicle routing and scheduling by the possibility of subcontracting a part of the requests to external carriers. This problem extension transforms the usual vehicle routing and scheduling problems to the more general integrated operational transportation problems. In this contribution, we analyze the motivation, the chances, the realization, and the challenges of the integrated operational planning and report on experiments for extending the plain Vehicle Routing Problem to a corresponding problem combining vehicle routing and request forwarding by means of different sub-contraction types. The extended problem is formalized as a mixed integer linear programming model and solved by a commercial mathematical programming solver. The computational results show tremendous costs savings even for small problem instances by allowing subcontracting. Additionally, the performed experiments for the operational transportation planning are used for an analysis of the decision on the optimal fleet size for own vehicles and regularly hired vehicles.

• 경영과학
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• 제18권2호
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• pp.125-134
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• 2001

This paper is concerned with the development of a GIS-based distribution system with service consideration. The proposed model could be used for a wide range of logistics applications in planning, engineering and operational purpose for logistics system. This research addresses the formulation of those complex prob1ems of two-echelon logistics system to plan the incorporating supply center locations and distribution problems based on GIS. We propose an integrated logistics model for determining the optimal patterns of supply centers and inventory allocations (customers) with a three-step sequential approach. 1) First step, Developing GIS-distance model and stochastic set-covering program to determine Optimel pattern of supply center location. 2) Second step, Optimal sector-clustering to support customers. 3) Third step, Optimal vehicle rouse scheduling based on GIS, GIS-VRP In this research we developed GUI-tree program, the GIS-VRP provide the vehicle to users and freight information in real time. We applied a set of sample examples to this model and demonstrated samp1e results. It has been found that the proposed model is potentially efficient and useful in solving multi-depot problem through examples. However the proposed model can provide logistics decision makers to get the best supply schedule.

• 산업경영시스템학회지
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• 제43권3호
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• pp.53-60
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• 2020

Evaluating the operational efficiency of electric vehicle charging stations (EVCSs) is important to understand charging network evolution and the charging behavior of electric vehicle users. However, aggregation of efficiency performance metrics poses a significant challenge to practitioners and researchers. In general, the operational efficiency of EVCSs can be measured as a complicated function of various factors with multiple criteria. Such a complex aspect of managing EVCSs becomes one of the challenging issues to measure their operational efficiency. Considering the difficulty in the efficiency measurement, this paper suggests a way to measure the operational efficiency of EVCSs based on data envelopment analysis (DEA). The DEA model is formulated as constant returns of output-oriented model with five types of inputs, four of them are the numbers of floating population and nearby charging stations, distance of nearby charging stations and traffic volume as desirable inputs and the other is the traffic speed in congestion as undesirable one. Meanwhile, the output is given by the charging frequency of EVCSs in a day. Using real-world data obtained from reliable sources, we suggest operational efficiencies of EVCSs in Seoul and discuss implications on the development of electric vehicle charging network. The result of efficiency measurement shows that most of EVCSs in Seoul are inefficient, while some districts (Nowon-gu, Dongdaemun-gu, Dongjak-gu, Songpa-gu, Guro-gu) have relatively more efficient EVCSs than the others.

• 한국경영과학회지
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• 제24권4호
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• pp.95-109
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• 1999

We propose a series of methodologies that can evaluate relative efficiency of logistics units(centers) in three categories; managerial, cost, and operational efficiency. Inputs and outputs of logistics systems are first defined. Appropriate quantitative and qualitative measures for the three categories are then selected. Employed also are Analytic Hierarchy Process, Weighted Scoring Method, Stochastic Frontier Model, and Data Envelopment Analysis for the development of a comprehensive assessment scheme. Our scheme not only assesses the degree of relative efficiency of logistics units but also identify the sources of inefficiency in each unit The methodologies are applied to a large telecommunications company which operates 12 distribution centers nation wide. Relative efficiencies of the centers are compared using 1995-1997 performance data. Summarized are the level of efficiency of each distribution center for each of the three categories. The degree and sources of inefficiency of each distribution center are also discussed.

• 한국항만경제학회지
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• 제27권3호
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• pp.13-39
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• 2011

공급사슬관리에 관한 많은 선행연구들이 지속적으로 공급사슬성과의 향상을 위해서는 협업이 필요하다고 주장하고 있다. 본 연구는 물류기업의 관계특성, 협업, 성과 간의 인과관계를 밝히는 것이며, 특히 관계특성과 성과 간의 관계에서 매개변수로서 두 종류의 협업(운영적 협업과 전략적 협업)에 초점을 맞추고 있다. 분석을 위해 물류기업 164개의 자료가 사용되었으며, PLS를 이용해 구조모형을 분석하였다. 분석결과 신뢰성, 정보공유는 운영적협업에 긍정적인 영향을 미쳤으며, 운영적 협업은 공급사슬 성과에 긍정적인 영향을 미치는 것으로 나타났다. 거래지속의지와 정보공유는 전략적 협업에 긍정적인 영향을 미쳤으나, 전략적 협업은 공급사슬 성과에 긍정적인 영향을 미치지 않는 것으로 나타났다. 따라서 관계 특성과 공급사슬성과 사이에는 운영적 협업이 매개역할을 하는 것으로 나타났다.

• 디지털융복합연구
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• 제15권9호
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• pp.167-178
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• 2017

빅데이터는 기업에게 있어 미래의 핵심자산이며 물류부문에도 새로운 경쟁력을 높일 수 있는 핵심적인 요소이다. 그러나 지금까지 물류에서 빅데이터를 어떻게 수집하고 분석하며 활용해야 할지에 대한 연구는 아직 부족하다. 이러한 상황에서 본 연구는 기존 선행연구와 DHL의 연구에서 나타난 물류에서의 빅데이터 분석 및 활용에 대한 결과를 바탕으로 물류기업에게 적용 가능한 하나의 가치모델을 개발하였다. 본 연구의 목적은 물류에서 빅데이터 분석의 활용을 통하여 물류기업의 운영효율성 및 고객경험의 극대화 수준을 향상키시고 빅데이터 활용에 따른 경쟁적 지위와 경쟁력을 향상시키고 새로운 사업기회를 개발하는 데에 있다. 이러한 연구는 물류부문에서 빅데이터 분석의 활용을 위한 가치모델을 새롭게 창출하는 의의가 있으며 향후 물류부문 뿐만 아니라 타 업종에도 적용가능한 시사점을 제공할 수 있다.

• 산업경영시스템학회지
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• 제46권spc호
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• pp.89-100
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• 2023

Industrial complexes are areas where manufacturing companies are integrated, and logistics between tenant companies play a very important role, but idle resources can occur depending on the situation if each company operates independently. Accordingly, this study aimed to reduce overall logistics costs and increase corporate productivity by looking at ways to share and utilize logistics resources such as warehouses and transportation equipment to efficiently utilize logistics resources in industrial complexes and implementing a logistics sharing platform that can share these idle resources. To this end, this study conducted a research survey on the logistics status of manufacturing companies in Ulsan-Mipo Industrial Complex, based on this analysis, the necessity of logistics resource types and utilization of industrial complex resident companies, and based on this, a service model for logistics resource sharing was studied. In addition, it was intended to analyze the operational characteristics of the existing logistics system to derive improvements and to derive optimal measures to utilize information on shared idle resources. This study confirmed the importance of sharing and utilizing idle resources to optimize logistics resources in industrial complexes, and is expected to contribute to reducing logistics costs and increasing logistics efficiency of tenant companies.

• 대한안전경영과학회지
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• 제25권4호
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• pp.141-151
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• 2023

Recently, due to the expansion of the logistics industry, demand for logistics automation equipment is increasing. The modern logistics industry is a high-tech industry that combines various technologies. In general, as various technologies are grafted, the complexity of the system increases, and the occurrence rate of defects and failures also increases. As such, it is time for a predictive maintenance model specialized for logistics automation equipment. In this paper, in order to secure the operational safety and reliability of the parcel loading system, a predictive maintenance platform was implemented based on the Naive Bayes-LSTM(Long Short Term Memory) model. The predictive maintenance platform presented in this paper works by collecting data and receiving data based on a RabbitMQ, loading data in an InMemory method using a Redis, and managing snapshot DB in real time. Also, in this paper, as a verification of the Naive Bayes-LSTM predictive maintenance platform, the function of measuring the time for data collection/storage/processing and determining outliers/normal values was confirmed. The predictive maintenance platform can contribute to securing reliability and safety by identifying potential failures and defects that may occur in the operation of the parcel loading system in the future.