Enforced environmental regulations call for extending the domain of manufacturers’ responsibility to the entire product life cycle. To comply with the environmental regulations, manufacturers have constructed reverse logistics networks to re-collect their leftover waste for recycling consumed resources. However, the operational activities associated with storage, loading and transportation processes within the networks inevitably impose environmental burdens. Particularly, the transportation process largely influences environmental performance due to perpetual uses of transportation vehicles. Therefore, there is a need to develop an environmentally- conscious transportation model that can efficiently manage the uses of transportation vehicles. Additionally, it is vital to analyze its significances of environmental performance to compare quantitatively it with existing models. This paper proposes a transportation model for improving environmental performance in a reverse logistics network. This paper also presents a case study to perform its comparative analysis using Life Cycle Assessment that evaluates potential environmental impacts of a product system.

To address global climate change, various governments are investing in electric vehicle research and, especially in Korea, the application of electric vehicles to public transportation. The lithium batteries used in electric vehicles typically have an exp

Expanded muti-source Weber problem (EWP), which introduced in this paper, is a reverse logistics network design problem to minimize the total transportation cost from customers thorough regional center to central center. Decision factor of EWP are the locations of regional centers and a central center. We introduce a GRASP heuristics for the EWP. In the suggested GRASP, an expanded iterative location allocation method (EILA) is introduced based on the Cooper's iterative location allocation method[3]. For the initial solution of GRASP, allocation first seed (AFSeed) and location first seed (LFSeed) are developed. The computational experiment for the objective value shows that the LFSeed is better than the AFSeed. Also the calculating time of the LFSeed is better than that of the AFSeed.

본 논문에서는 수명이 다한 제품이나 소비지-가 더 이상 사용하지 않는 폐기품을 다시 재사용하거나 폐기하는데 필요한 일련의 활동을 위한 역방향 로지스틱스에서의 수거망 설계 문제를 다루고 있다 수거망 설계 문제는 수거지점의 위치와 수요지의 폐기품을 수거 지점에 할당하는 것을 결정하는 문제로 정의할 수 있으며 수거지점은 재활용품이나 폐기품이 위치한 지접 근처에 위치하고 주어진 잠재적인 위치들 중에서 결정하게 된다. 여기서，각 수거지점은 용량제약이 있어 수거

Reverse logistics is the process of planning and controlling the recovery flow of end of life products Industry is increasingly being confronted with the need to solve several reverse logistics issues because of not only stringent environmental legislatio

Recently, an industrial production-distribution planning problem has been widely investigated in Supply Chain Management(SCM). One of the key issues in the current SCM research area is reverse logistics network. This study have developed a simulation model for the reverse logistics network. The simulation model analysis reverse logistics network issues such as inventory policy, manufacturing policy, transportation mode, warehouse assignment, supplier assignment. Computational experiments using commercial simulation tool ARENA show that the real problems. The model can be used to decide an appropriate production-distribution planning problem in the research area.

The Balanced scorecard has been evolved in various function. In the various functional Balanced scorecard, this paper focuses on the reverse logistics BSC, and the decision the weights of Key Performance Indicators. In this paper, a combination of Balanced scorecard and value evaluation based approach proposed multi-criteria provides a more accurate representation of the problem for measuring company.

The studies on the logistics has been mainly centered on the logistics information system and logistics performance on the supply chain for the enterprise's profit making. For sustainable development, it's being required the construction of recycling-oriented system, and it's also necessary to construct the efficient system not only in forward but in reverse channel. In addition, it's required to construct information system for supporting reverse logistics smoothly. In this study of manufacturing enterprises, recognition on the environmental problems is set as the adaptation degree to the national environmental regulations and enterprise's concern to the environmental logistics, and it presents the direction through analyzing the effects of such environmental logistics recognition on reverse logistics information system and performance. In order to achieve these aims, it was performed through combining philological and positive studies.

If do not become whole optimization because enterprise's individual enterprise internal determinate improvement effort is associated with activity in enterprise SCM, competitive power can not but be extremely limited the result. Therefore, to spur in hidden cost's discovery and logistics' optimization is actuality. In this paper, as long as it is by logistics cost except empty driving if reverse logistics happens in distribution channel progressing, logistics reverse logistics' hidden cost through model that do minimization profit of logistics to look for plan that can do maximization try. Finally, is based on dual of distribution cost and profit of logistics and reverse logistics and achieves Pull, optimal system modeling that use Push system and gropes method of effective logistics cost.

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.

공급망사슬관리(Supply Chain Management : SCM)의 기법이 도입되어 운영되는 한편에서는 최근의 RFID(Ratio Frequency IDentification)의 활용등 SCM, VMI의 Visibility 향상과 유비쿼터스 비즈니스 환경의 실현을 가능하게 하는 신기술들의 상용화가 일부 선진국에서는 기업들의 RFID 기술접목 도입등에 힘입어 더욱 빨라질 것으로 전망된다. 특히 SCM 간의 정보공유와 협력을 바탕으로 고객관리, 서비스, 수요예측, 구매, 마케팅, 물류, 재고관리 전반을 효율화함과 동시에 RFID의 신기술을 접목하는 IT시스템 도입으로의 발전은 피할 수 없는 우리 기업의 경영전략이 되었다. 본 연구의 목적은 유통업체와 제조업체의 재고운영을 위한 재고관리, 결품방지의 효과에 대한 실태를 분석하고 KPI지수 요인과, 수요예측과의 상관관계를 검증, 고찰하여 재고운영에 관한 문제점과 해결방안을 모색하고 더 나아가 RFID 신기술 접목을 위한 환경모델을 제시하고자 한다.

  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

Recently, shifting channel power is forcing supply chain to take back products As you can Imagine returned product has always been a problem for all parties in the supply chain due to the disruption in operations and a headache In proc-essing returned pro