• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.26 no.3D
• /
• pp.361-366
• /
• 2006

It is widely known that the dynamic optimal path algorithm, adopting real-time path finding, can be supporting an optimal route with which users are satisfied economically and accurately. However, this system has to search optimal routes frequently for updating them. The proposed concept of optimizing search area lets it reach heuristic optimal path rapidly and efficiently. Since optimal path should be increased in proportion to an distance between origin and destination, tremendous calculating time and highly efficient computers are required for searching long distance journey. In this paper, as a result of which the concepts of partial solution and representative path are suggested. It was possible to find an optimal route by decreasing a half area in comparison with the previous method. Furthermore, as the size of the searching area is uniform, comparatively low efficient computer is required for long distance trip.

• Transactions of the Korean Society of Mechanical Engineers
• /
• v.19 no.4
• /
• pp.887-895
• /
• 1995

Considering that the laser range finder has the excellent resolution with respect to angular and distance measurements, a sophisticated local path planning algorithm is achieved by subgoal and sub-subgoal searching methods. The subgoal searching finds the passable ways between obstacles and selects the optimal pathway in order to reduce the moving distanced from start point to given to given goal. On the other hand, the sub-subgoal searching corrects the path given in subgoal searching in the case of which the mobile robot will collide with obstacles. Also, the effectiveness of the established local path planning and local minimum avoiding algorithm are estimated by computer simulation and experimentation in complex environment.

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

• Journal of the Korean Operations Research and Management Science Society
• /
• v.8 no.1
• /
• pp.11-18
• /
• 1983

This paper shows a new efficient solution method of finding an optimal path for a cruise missile or aircraft to a target which has the maximal survivability and penetration effectiveness against sophisticated defenses and over varied terrain. We first generate a grid structure over the terrain, to construct a network. Since our network usually has about 10,000 nodes, the conventional Dijkstra algorithm takes too much computational time in its searching process for a new permanent node. Our method utilizes the Hashing technique to reduce the computational time of the searching process. Extensive computational results are presented.

• 한국ITS학회:학술대회논문집
• /
• 2004.11a
• /
• pp.349-354
• /
• 2004

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.18 no.5
• /
• pp.91-99
• /
• 2019

Existing node-to-node based optimal path searching is built on the assumption that all destination nodes can be arrived at from an origin node. However, the recent appearance of the adaptive path search algorithm has meant that the optimal path solution cannot be derived in node-to-node path search. In order to reflect transportation data at the links in real-time, the necessity of the node-to-link (or link-to-node; NL) problem is being recognized. This research assumes existence of a network with link-label and non-additive path costs as a solution to the node-to-link optimal path problem. At the intersections in which the link-label has a turn penalty, the network retains its shape. Non-additive path cost requires that M-similar paths be enumerated so that the ideal path can be ascertained. In this, the research proposes direction deletion and turn restriction so that regulation of the loop in the link-label entry-link-based network transformation method will ensure that an optimal solution is derived up until the final link. Using this method on a case study shows that the proposed method derives the optimal solution through learning. The research concludes by bringing to light the necessity of verification in large-scale networks.

• Proceeding of EDISON Challenge
• /
• 2015.03a
• /
• pp.479-483
• /
• 2015

In case of the big city, choosing the adequate root of which we can reach the destination can affect the driver's condition and driving time. so it is quite important to find the optimal routes for arriving the destination as considering the factors, such as driving conditions or travel time and so on. In this paper, we develop route choice model with considering driving conditions and travel time, and it can search the optimal path which make drivers reduce their fatigues using genetic algorithm.

• The KIPS Transactions:PartD
• /
• v.16D no.1
• /
• pp.113-122
• /
• 2009

Since the traditional pattern mining methods only probe unspecified moving patterns that seem to satisfy users' requests among diverse patterns within the limited scopes of time and space, they are not applicable to problems involving the mining of optimal moving patterns, which contain complex time and space constraints, such as 1) searching the optimal path between two specific points, and 2) scheduling a path within the specified time. Therefore, in this paper, we illustrate some problems on mining the optimal moving patterns with complex time and space constraints from a vast set of historical data of numerous moving objects, and suggest a new moving pattern mining method that can be used to search patterns of an optimal moving path as a location-based service. The proposed method, which determines the optimal path(most frequently used path) using pattern frequency retrieved from historical data of moving objects between two specific points, can efficiently carry out pattern mining tasks using by space generalization at the minimum level on the moving object's location attribute in consideration of topological relationship between the object's location and spatial scope. Testing the efficiency of this algorithm was done by comparing the operation processing time with Dijkstra algorithm and $A^*$ algorithm which are generally used for searching the optimal path. As a result, although there were some differences according to heuristic weight on $A^*$ algorithm, it showed that the proposed method is more efficient than the other methods mentioned.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.28 no.8A
• /
• pp.581-590
• /
• 2003

This paper proposes the routing path selection mechanism for source routing-based PtMP (Point-to-Multipoint) call in ATM switching system. Especially, it suggests PtMP routing path selection method that can share the maximum resource prior to the optimal path selection, guarantee the reduction of path calculation time and cycle prevention. The searching for the nearest branch point from destination node to make the maximum share of resource is the purpose of this algorithm. Therefore among neighbor nodes from destination node by back-tracking, this algorithm fixes the node crossing first the node on existing path having the same Call ID as branch node, constructs the optimal PtMP routing path. The optimal node to be selected by back-tracking is selected by the use of Dijkstra algorithm. That is to say, PtMP routing path selection performs the step of cross node selection among neighboring nodes by back-tracking and the step of optimal node selection(optimal path calculation) among neighboring nodes by back-tracking. This technique reduces the process of search of routing information table for path selection and path calculation, also solves the cycle prevention easily during path establishment.

• Journal of the Korean Operations Research and Management Science Society
• /
• v.37 no.4
• /
• pp.95-109
• /
• 2012

Being able to quickly locate valuable medical equipment is critical inside hospitals. In order to utilize limited budget and resources efficiently, accurate locating or tracking is required in many fields. In this research, we focus on how to find the location of missing assets by using RFID in real time indoors to track equipment. When equipment needs to be searched, the purpose of a RFID device is to minimize the time, investment cost and effort spent searching for the equipment. Thus, this research presents a mathematical model of using RFID (both handheld reader and stationary reader) for efficient asset location. We derive the expected time of locating RFID-tagged objects in a multi-area environment where hand-held RF readers are used. We then discuss where to deploy stationary RF readers in order to maximize the efficiency of the search process.