• Journal of the Korea Society of Computer and Information
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• v.24 no.1
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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.

• IE interfaces
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• v.22 no.2
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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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• 2004.08a
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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.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.12
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• pp.1720-1725
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• 2019

In this paper, we consider the efficiency of the scheme for for routing summary algorithms in discontiguous networks. Router than updating and transmitting the entire subnet information in the routing protocol, only the shortened update information is sent and the routing table is shortened to make the router resources more efficient and improve network stability and performance. However, if a discontiguous network is formed in the network design process, a problem arises due to the network contraction function and does not bring about the result of fundamental router efficiency. Using different major networks subnets one major network, causing problems in communication and routing information exchange if the configuration is incorrect. The algorithm proposed in this paper removes only the auto-summary algorithm from the existing algorithm, which increases the complexity and stability of the routing table and reduces the CPU utilization of network equipment from 16.5% to 6.5% Confirmed.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.10A
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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.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37B no.9
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• pp.760-766
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• 2012

In this paper, we propose an efficient flooding process on link-state routing protocol. It is possible to exchange information using typical link-state routing protocol; for example, OSPF(Open Short Path First) or IS-IS(Intermediate system routing protocol) that floods LSA between nodes when the network topology change occurs. However, while the scale of network is getting bigger, it affects the network extensibility because of the unnecessary LSA that causes the increasing utilization of CPU, memory and bandwidth. An existing algorithm based on the Minimum spanning tree has both network instability and inefficient flooding problem. So, we propose algorithm for efficient flooding while maintaining network stability. The simulation results show that the flooding of proposed algorithm is more efficient than existing algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38A no.12
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• pp.1054-1060
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• 2013

This paper proposes a vehicle ad-hoc network (VANET) routing algorithm to reduce the probability of routing path discontinuity in urban intersections. In urban intersections, the vehicles may frequently change their moving directions. It can cause the disconnection of routing path and the increase of a packet transmission delay. In order to resolve this problem, the proposed routing algorithm exploits the information of moving directions in urban intersections. In this way, the proposed algorithm can reduce the probability of the local maximum which causes the increase of the number of routing hops and packet transmission delay. Simulation results show that the proposed algorithm can reduce the local maximum probability by 10% and increase the successful packet transmission ratio by 5% compared to the conventional VANET routing algorithms.

• IEMEK Journal of Embedded Systems and Applications
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• v.19 no.2
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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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• v.12 no.3
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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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• v.3 no.4
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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.