• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1846-1850
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• 2005

This paper presents a constrained-based routing (CBR) algorithm called, Dynamic Possible Path per Link (D-PPL) routing algorithm, for MultiProtocol Label Switching (MPLS) networks. In MPLS on-line routing, future traffics are unknown and network resource is limited. Therefore many routing algorithms such as Minimum Hop Algorithm (MHA), Widest Shortest Path (WSP), Dynamic Link Weight (DLW), Minimum Interference Routing Algorithm (MIRA), Profiled-Based Routing (PBR), Possible Path per Link (PPL) and Residual bandwidth integrated - Possible Path per Link (R-PPL) are proposed in order to improve network throughput and reduce rejection probability. MIRA is the first algorithm that introduces interference level avoidance between source-destination node pairs by integrating topology information or address of source-destination node pairs into the routing calculation. From its results, MIRA improves lower rejection probability performance. Nevertheless, MIRA suffer from its high routing complexity which could be considered as NP-Complete problem. In PBR, complexity of on-line routing is reduced comparing to those of MIRA, because link weights are off-line calculated by statistical profile of history traffics. However, because of dynamic of traffic nature, PBR maybe unsuitable for MPLS on-line routing. Also, both PPL and R-PPL routing algorithm we formerly proposed, are algorithms that achieve reduction of interference level among source-destination node pairs, rejection probability and routing complexity. Again, those previously proposed algorithms do not take into account the dynamic nature of traffic load. In fact, future traffics are unknown, but, amount of previous traffic over link can be measured. Therefore, this is the motivation of our proposed algorithm, the D-PPL. The D-PPL algorithm is improved based on the R-PPL routing algorithm by integrating traffic-per-link parameters. The parameters are periodically updated and are dynamically changed depended on current incoming traffic. The D-PPL tries to reserve residual bandwidth to service future request by avoid routing through those high traffic-per-link parameters. We have developed extensive MATLAB simulator to evaluate performance of the D-PPL. From simulation results, the D-PPL improves performance of MPLS on-line routing in terms of rejection probability and total throughput.

• Journal of Korean Society of Transportation
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• v.14 no.3
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• pp.45-59
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• 1996

The shortest path algorithm for route guidance is implicitly required not only to support geometrical variations of transportation network such as U-TURN or P-TURN but to efficiency search reasonable routes in searching mechanism. The purpose of this paper is to integrate such two requirements ; that is, to allow U-TURN and P-TURN possibilities and to cut down searching time in locating routes between two points (origin and destination) in networks. We also propose a new type of link searching algorithm which can solve the limitation of vine building algorithm at consecutively left-turn prohibited intersections. The test site is a block of Gangnam road network that has some left-turn prohibited and allowed U-TURN intersections. Four models have been identified to be comparatively analyzed in terms of searching efficiency. The Models are as follows : (i) Model 1 - Link Searching Dijkstra Algorithm without Searching Area Extraction (SAE) ; (ii) Model 2 - Link Searching Dijkstra Algorithm with SAE ; (iii) Model 3 - Link Searching Bidirectional Dijkstra Algorithm without SAE ; and (iv) Model 4 - Link Searching Bidirectional Dijkstra Algorithm with SAE. The results of comparative evaluation show that Model 4 can effectively find optimum path faster than any other models as expected. Some discussions and future research agenda have been presented in the light of dynamic route guidance application of the urban ATIS.

• Journal of Korean Society of Transportation
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• v.22 no.6
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• pp.101-108
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• 2004

The new transit fare in the Seoul Metropolitan is basically determined based on the distance-based fare system (DBFS). The total fare in DBFS consists of three parts- (1) basic fare, (2) transfer fare, and (3) extra fare. The fixed amount of basic fare for each mode is charged when a passenger gets on a mode, and it proceeds until traveling within basic travel distance. The transfer fare may be added when a passenger switches from the present mode to another. The extra fare is imposed if the total travel distance exceeds the basic travel distance, and after that, the longer distance the more extra fare based on the extra-fare-charging rule. This study proposes an algorithm for finding minimum fare route in DBFS. This study first exploits the link-label-based searching method to enable shortest path algorithms to implement without network expansion at junction nodes in inter-modal transit networks. Moreover, the link-expansion technique is adopted in order for each mode's travel to be treated like duplicated links, which have the same start and end nodes, but different link features. In this study, therefore, some notations associated with modes can be saved, thus the existing link-based shortest path algorithm is applicable without any loss of generality. For fare calculation as next steps, a mathematical formula is proposed to embrace fare-charging process using search process of two adjacent links illustrated from the origin. A shortest path algorithm for finding a minimum fare route is derived by converting the formula as a recursive form. The implementation process of the algorithm is evaluated through a simple network test.

• Journal of the Korean Society of Hazard Mitigation
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• v.11 no.3
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• pp.49-56
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• 2011

This paper deals with a methodology for searching optimal route of hazard material (hazmat) vehicles. When we make a decision of hazmat optimal paths, there is a conflict between the public aspect which wants to minimize risk and the private aspect which has a goal of minimizing travel time. This paper presents Efficient Vector Labeling algorithm as a methodology for searching optimal path of hazmat transportation, which is intrinsically one of the multi-criteria decision making problems. The output of the presented algorithm is a set of Pareto optimal paths considering both risk and travel time at a time. Also, the proposed algorithm is able to identify non-dominated paths which are significantly different from each other in terms of links used. The proposed Efficient Vector Labeling algorithm are applied to test bed network and compared with the existing k-shortest path algorithm. Analysis of result shows that the proposed algorithm is more efficient and advantageous in searching reasonable alternative routes than the existing one.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.1140-1143
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• 1996

A new approach based on artificial potential function is proposed for the obstacle avoidance of redundant manipulators. Unlike the so-called "global" path planning method, which requires expensive computation for the path search before the manipulator starts to move, this new approach, "local" path planning, researches the path in real-time using the local distance information. Previous use of artificial potential function has exhibited local minima in some complex environments. This thesis proposes a potential function that has no local minima even for a cluttered environment. This potential function has been implemented for the collision avoidance of a redundant robot in Simulation. The simulation also employ an algorithm that eliminates collisions with obstacles by calculating the repulsive potential exerted on links, based on the shortest distance to object.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.12C
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• pp.1215-1227
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• 2002

This paper presents a genetic algorithmic approach to shortest path (SP) routing problem. Variable-length chromosomes (strings) and their genes (parameters) have been used for encoding the problem. The crossover operation that exchanges partial chromosomes (partial-routes) at positionally independent crossing sites and the mutation operation maintain the genetic diversity of the population. The proposed algorithm can cure all the infeasible chromosomes with a simple repair function. Crossover and mutation together provide a search capability that results in improved quality of solution and enhanced rate of convergence. Computer simulations show that the proposed algorithm exhibits a much better quality of solution (route optimality) and a much higher rate of convergence than other algorithms. The results are relatively independent of problem types (network sizes and topologies) for almost all source-destination pairs.

• Journal of Communications and Networks
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• v.18 no.4
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• pp.559-566
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• 2016

Software defined network (SDN) can effectively improve the performance of traffic engineering and will be widely used in backbone networks. Therefore, new energy-saving schemes must take SDN into consideration; this action is extremely important owing to the rapidly increasing energy consumption in telecom and Internet service provider (ISP) networks. Meanwhile, the introduction of SDN in current networks must be incremental in most cases, for technical and economic reasons. During this period, operators must manage hybrid networks in which SDN and traditional protocols coexist. In this study, we investigate the energy-efficient traffic engineering problem in hybrid SDN/Internet protocol (IP) networks. First, we formulate the mathematical optimization model considering the SDN/IP hybrid routing mode. The problem is NP-hard; therefore, we propose a fast heuristic algorithm named hybrid energy-aware traffic engineering (HEATE) as a solution. In our proposed HEATE algorithm, the IP routers perform shortest-path routing by using distributed open shortest path first (OSPF) link weight optimization. The SDNs perform multipath routing with traffic-flow splitting managed by the global SDN controller. The HEATE algorithm determines the optimal setting for the OSPF link weight and the splitting ratio of SDNs. Thus, the traffic flow is aggregated onto partial links, and the underutilized links can be turned off to save energy. Based on computer simulation results, we demonstrate that our algorithm achieves a significant improvement in energy efficiency in hybrid SDN/IP networks.

• The Journal of Bigdata
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• v.7 no.2
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• pp.129-137
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• 2022

With the development of the 4th industry, the logistics industry is evolving into a smart logistics system. However, ship work that transports vehicles is progressing slowly due to various problems. In this paper, we propose an stowage automation algorithm that can be used for cargo loading of vehicle carriers that shortens loading and unloading work time. The stowage automation algorithm returns the shortest distance by searching for a loading space and a movable path in the ship in consideration of the structure of the ship. The algorithm identifies walls, ramps and vehicles that have already been shipped, and can work even with randomly placed. In particular, it is expected to contribute to developing a smart logistics system for vehicle carriers by referring to the ship's master plan to search for vehicle loading and unloading space in each port and predict the shortest movable path.

• Journal of Korean Society for Geospatial Information Science
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• v.20 no.2
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• pp.23-29
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• 2012

Existing pedestrian and evacuation models generally seek to find locally optimal solutions for the shortest or the least time paths to exits from individual locations considering pedestrian's characteristics (eg. speed, direction, sex, age, weight and size). These models are not designed to produce globally optimal solutions that reduce the total evacuation time of the entire pedestrians in a building when all of them evacuate at the same time. In this study, we suggest a globally optimal model for indoor pedestrian evacuation to minimize the total evacuation time of occupants in a building considering different distributions of them. We used the genetic algorithm, one of meta-heuristic techniques because minimizing the total evacuation time can not be easily solved by polynomial expressions. We found near-optimal evacuation path and time by expressing varying pedestrians distributions using chromosomes and repeatedly filtering solutions. In order to express and experiment our suggested algorithm, we used CA(cellular automata)-based simulator and applied to different indoor distributions and presented the results.

• Korean Journal of Computational Design and Engineering
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• v.6 no.3
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• pp.174-183
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• 2001

This study proposes an improved genetic algorithm (GA) to derive solutions for facility layout problems having inner walls and passages. The proposed algorithm models the layout of facilities on a flour-segmented chromosome. Improved solutions are produced by employing genetic operations known as selection, crossover, inversion, mutation, and refinement of these genes for successive generations. All relationships between the facilities and passages are represented as an adjacency graph. The shortest path and distance between two facilities are calculated using Dijkstra's algorithm of graph theory. Comparative testing shows that the proposed algorithm performs better than other existing algorithm for the optimal facility layout design. Finally, the proposed algorithm is applied to ship compartment layout problems with the computational results compared to an actual ship compartment layout.