• 한국컴퓨터정보학회논문지
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• 제24권1호
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• pp.167-178
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• 2019

In this paper, we study the multi-objectives vehicle and drone routing problem with time windows, MOVDRPTW for short, which is defined in an urban delivery network. We consider the dual modal delivery system consisting of drones and vehicles. Drones are used as a complement to the vehicle and operate in a point to point manner between the depot and the customer. Customers make various requests. They prefer to receive delivery services within the predetermined time range and some customers require fast delivery. The purpose of this paper is to investigate the effectiveness of the delivery strategy of using drones and vehicles together with a multi-objective measures. As experiment datasets, we use the instances generated based on actual courier delivery data. We propose a hybrid multi-objective evolutionary algorithm for solving MOVDRPTW. Our results confirm that the vehicle-drone mixed strategy has 30% cost advantage over vehicle only strategy.

• 산업공학
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• 제22권2호
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• pp.153-164
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• 2009

An effective management for reverse flows of products such as reuse, repair and disposal, has become an important issue for every aspect of business. In this paper, we study the Location-Routing Problem (LRP) in the multi-stage closed-loop supply chain network. The closed-loop supply chain in this study integrated both forward and reverse flows. In forward flow, a factory, Distribution Center (DC) and retailer are considered as usual. Additionally in reverse flow, we consider the Central Returns collection Center (CRC) and disposal facility. We propose a mixed integer programming model for the design of closed-loop supply chain integrating both forward and reverse flows. Since the LRP belongs to an NP-hard problem, we suggest a heuristic algorithm based on genetic algorithm. For some test problems, we found the optimal locations and routes by changing the numbers of retailers and facility candidates. Furthermore, we compare the efficiencies between open-loop and closed-loop supply chain networks. The results show that the closed-loop design is better than the open one in respect to the total routing distance and cost. This phenomenon enlarges the cut down effect on cost as an experimental space become larger.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2004년도 ICCAS
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• pp.772-776
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• 2004

This paper proposes an interference avoidance approach for Constraint-Based Routing (CBR) algorithm in the Multi-Protocol Label Switching (MPLS) network. The MPLS network itself has a capability of integrating among any layer-3 protocols and any layer-2 protocols of the OSI model. It is based on the label switching technology, which is fast and flexible switching technique using pre-defined Label Switching Paths (LSPs). The MPLS network is a solution for the Traffic Engineering(TE), Quality of Service (QoS), Virtual Private Network (VPN), and Constraint-Based Routing (CBR) issues. According to the MPLS CBR, routing performance requirements are capability for on-line routing, high network throughput, high network utilization, high network scalability, fast rerouting performance, low percentage of call-setup request blocking, and low calculation complexity. There are many previously proposed algorithms such as minimum hop (MH) algorithm, widest shortest path (WSP) algorithm, and minimum interference routing algorithm (MIRA). The MIRA algorithm is currently seemed to be the best solution for the MPLS routing problem in case of selecting a path with minimum interference level. It achieves lower call-setup request blocking, lower interference level, higher network utilization and higher network throughput. However, it suffers from routing calculation complexity which makes it difficult to real task implementation. In this paper, there are three objectives for routing algorithm design, which are minimizing interference levels with other source-destination node pairs, minimizing resource usage by selecting a minimum hop path first, and reducing calculation complexity. The proposed CBR algorithm is based on power factor calculation of total amount of possible path per link and the residual bandwidth in the network. A path with high power factor should be considered as minimum interference path and should be selected for path setup. With the proposed algorithm, all of the three objectives are attained and the approach of selection of a high power factor path could minimize interference level among all source-destination node pairs. The approach of selection of a shortest path from many equal power factor paths approach could minimize the usage of network resource. Then the network has higher resource reservation for future call-setup request. Moreover, the calculation of possible path per link (or interference level indicator) is run only whenever the network topology has been changed. Hence, this approach could reduce routing calculation complexity. The simulation results show that the proposed algorithm has good performance over high network utilization, low call-setup blocking percentage and low routing computation complexity.

• 한국정보통신학회논문지
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• 제23권12호
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• pp.1720-1725
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• 2019

본 논문에서는 불연속 네트워크(discontiguous network)의 라우팅 축약기능(summary) 알고리즘에 대한 방식의 효율화에 대해 고찰을 한다. 서로 다른 전체의 서브넷 정보를 업데이트하여 전송하는 것보다 네트워크 정보를 축약하여 축약된 업데이트 정보만 전송하면 라우팅 테이블의 축약으로 라우터의 자원의 효율화가 이루어 지며 네트워크 안정과 성능을 향상시킬 수 있다. 그러나 네트워크 설계과정에서 불연속적인 네트워크가 구성될 경우 네트워크 축약 기능으로 문제가 발생되며 근본적인 라우터의 효율화의 결과를 가져오지 못한다. 본 논문에서 제안하는 알고리즘은 자동 축약 알고리즘의 단점을 보완한 알고리즘으로, 이로 인해 라우팅 테이블의 안정성을 높이고 그 결과 네트워크 장비의 CPU Utilization을 기존 16.5%에서 6.5%까지 낮추어 효율화가 구현됨을 확인하였다.

• 한국통신학회논문지
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• 제32권10A호
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• pp.1023-1033
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• 2007

This study considers a joint congestion control, routing and power control for energy-constrained wireless networks. A mathematical model is introduced which includes maximization of network utility, maximization of network lifetime, and trade-off between network utility and network lifetime. The framework would maximize the overall throughput of the network where the overall throughput depends on the data flow rates which in turn is dependent on the link capacities. The link capacity on the other hand is a function of transmit power levels and link Signal-to-Interference-plus-Noise-Ratio (SINR) which makes the power allocation problem inherently difficult to solve. Using dual decomposition techniques, subgradient method, and logarithmic transformations, a joint algorithm for rate and power allocation problems was formulated. Numerical examples for each optimization problem were also provided.

• 한국통신학회논문지
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• 제37B권9호
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• pp.760-766
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• 2012

본 논문에서 효율적인 플러딩(flooding)을 위한 알고리즘을 제시하였다. 대표적인 link-state 라우팅 프로토콜인 OSPF(Open Short Path First)와 IS-IS(Intermediate System Routing Protocol)는 네트워크의 환경이 변할 때 노드 간에 LSA를 플러딩하여, 정보를 교환할 수 있다. 하지만 네트워크의 규모가 커지면 불필요한 LSA가 증가하여 CPU, 메모리, 대역폭 사용을 증가시켜 네트워크의 확장성에 영향을 준다. MST(Minimum spanning tree)를 기반으로 하는 기존 알고리즘은 네트워크의 불안정성과 효율적이지 못한 플러딩 문제를 가지고 있다. 그래서 네트워크의 안정성을 유지하면서 효율적인 플러딩을 위한 알고리즘을 제안하였다. 시뮬레이션을 통해 제안한 알고리즘이 기존 알고리즘보다 플러딩 효율이 향상된 것을 확인하였다.

• 한국통신학회논문지
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• 제38A권12호
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• pp.1054-1060
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• 2013

본 논문에서는 도심 교차로에서 경로 이탈 확률을 낮추어 줄 수 있는 차량 통신용 라우팅 알고리즘을 제안한다. 차량이 밀집된 도심의 교차로 지역에서는 차량들의 방향 전환으로 잦은 네트워크 단절과 패킷 전송지연 문제를 발생 시킬 수 있다. 본 논문에서는 이러한 문제점을 개선하기 위해 전송 노드 선정 과정에서 같은 진행방향의 노드를 이웃 노드로 선정하여 교차로에서 네트워크 단절의 비율을 낮출 수 있는 VANET (Vehicular Ad-hoc Network)용 라우팅 알고리즘을 제안한다. 시뮬레이션을 통한 성능분석 결과는 제안하는 알고리즘이 기존 라우팅 알고리즘에 비해 도심 교차로에서 경로 이탈 확률을 약 10% 감소시키며 네트워크 단절 비율을 5% 감소시킴을 보인다.

• 대한임베디드공학회논문지
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• 제19권2호
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• pp.107-114
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• 2024

Mobile ad hoc networks represent self-configuring networks of mobile devices that communicate without relying on a fixed infrastructure. However, traditional routing protocols in such networks encounter challenges in selecting efficient and reliable routes due to dynamic nature of these networks caused by unpredictable mobility of nodes. This often results in a failure to meet the low-delay and low-energy consumption requirements crucial for such networks. In order to overcome such challenges, our paper introduces a novel multi-objective and adaptive routing scheme based on the Q-learning reinforcement learning algorithm. The proposed routing scheme dynamically adjusts itself based on measured network states, such as traffic congestion and mobility. The proposed approach utilizes Q-learning to select routes in a decentralized manner, considering factors like energy consumption, load balancing, and the selection of stable links. We present a formulation of the multi-objective optimization problem and discuss adaptive adjustments of the Q-learning parameters to handle the dynamic nature of the network. To speed up the learning process, our scheme incorporates informative shaped rewards, providing additional guidance to the learning agents for better solutions. Implemented on the widely-used AODV routing protocol, our proposed approaches demonstrate better performance in terms of energy efficiency and improved message delivery delay, even in highly dynamic network environments, when compared to the traditional AODV. These findings show the potential of leveraging reinforcement learning for efficient routing in ad hoc networks, making the way for future advancements in the field of mobile ad hoc networking.

• Journal of Communications and Networks
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• 제12권3호
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• pp.246-252
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• 2010

A binary linear integer program is formulated for the problem of expanding the capacity of a fiber optic network and routing the traffic to deliver new interactive multimedia services. A two-phase Lagrangian dual search procedure and a Lagrangian heuristic are developed. Computational results show superior performance of the two-phase subgradient optimization compared with the conventional one-phase approach.

• Journal of Multimedia Information System
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• 제3권4호
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• pp.129-134
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• 2016

A routing protocol in mobile ad hoc networks is important, and a location based routing has attracted attention. We have proposed a method, in which plural mobile agents (MA) manage location information and construct a route and the number of MA dynamically changes depending on the network situation. However, the area where each MA manages is not always appropriate. This would increase the network load due to unnecessary split and mergence of MAs. To solve this problem, in this paper, we propose an enhanced method. In this method, the MA management area is properly determined based on distribution of nodes. From the performance evaluation, we show that the proposed method outperforms conventional methods in terms of packet delivery rate when network load is high.