• Journal of Ocean Engineering and Technology
• /
• v.20 no.1 s.68
• /
• pp.69-76
• /
• 2006

The design of efficient search path to maximize the Cumulative Detection Probability(CDP) is mainly dependent on experience and intuition when searcher detect the target using SONAR in the ocean. Recently with the advance of modeling and simulation method, it has been possible to access the optimization problems more systematically. In this paper, a method for the optimal search path calculation is developed based on the combination of the genetic algorithm and the calculation algorithm for detection range. We consider the discrete system for search path, space, and time, and use the movement direction of the SONAR for the gene of the genetic algorithm. The developed algorithm, OASPP(Optimal Acoustic Search Path Planning), is shown to be effective, via a simulation, finding the optimal search path for the case when the intuitive solution exists. Also, OASPP is compared with other algorithms for the measure of efficiency to maximize CDP.

• The Transactions of the Korean Institute of Electrical Engineers D
• /
• v.54 no.3
• /
• pp.148-155
• /
• 2005

A seam-line determination algorithm is proposed to determine image border-line in mosaicing using the transformation of gray value differences and dynamic programming. Since visually good border-line is the one along which pixel differences are as small as possible, it can be determined in association with an optimal path finding algorithm. A well-known effective optimal path finding algorithm is the Dynamic Programming (DP). Direct application of the dynamic programming to the seam-line determination causes the distance effect, in which seam-line is affected by its length as well as the gray value difference. In this paper, an adaptive cost transform algorithm with which the distance effect is suppressed is proposed in order to utilize the dynamic programming on the transformed pixel difference space. Also, a figure of merit which is the summation of fixed number of the biggest pixel difference on the seam-line (SFBPD) is suggested as an evaluation measure of seamlines. The performance of the proposed algorithm has been tested in both quantitively and visually on various kinds of images.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.15 no.3
• /
• pp.60-67
• /
• 2016

In cumulative transfer functions, as number of transfer increase, the impact of individual transfer to transfer cost increase linearly or non linearly. This function can effectively explain various passengers's travel behavior who choose their travel routes in integrated transit line networks including bus and railway modes. Using the function, it is possible to simulate general situations such that even though more travel times are expected, less number of transfer routes are preferred. However, because travel cost with cumulative transfer function is known as non additive cost function types in route search algorithms, finding an optimal route in integrated transit networks is confronted by the insolvable enumeration of all routes in many cases. This research proposes a methodology for finding an optimal path considering cumulative transfer function. For this purpose, the reversal phenomenon of optimal path generated in route search process is explained. Also a heuristic methodology for selecting an optimal route among multiple routes predefined by the K path algorithm. The incoming link based entire path deletion method is adopted for finding K ranking path thanks to the merit of security of route optimality condition. Through case studies the proposed methodology is discussed in terms of the applicability of real situations.

• Journal of Korea Multimedia Society
• /
• v.5 no.6
• /
• pp.745-752
• /
• 2002

A* algorithm is widely used in optimal car route search which is a kind of informed search, since the locations of starting and ending points are known a priori. Unidirectional A* algorithm requires considerable search time but guarantees a optimal path, bidirectional A* algorithm does not guarantee a optimal path and takes even longer search time than unidirectional search to guarantee a optimal path. In this paper, a new bidirectional A* algorithm which requites less search time and guarantees a optimal path is proposed. To evaluate the efficiency of the proposed algorithm, several experiments are conducted in real road map and the results show that the algorithm is very effective in terms of finding a optimal path and search time.

• Proceedings of the KIEE Conference
• /
• 2001.07d
• /
• pp.2417-2419
• /
• 2001

A path planning is one of the main subjects in a mobile robot. It is divided into two parts. One is a global path planning and another is a local path planning. This paper, using the formal two methods, presents that the mobile robot moves to multi-targets with avoiding unknown obstacles. For the shortest time and the lowest cost, the mobile robot has to find a optimal path between targets. To find a optimal global path, we used GA(Genetic Algorithm) that has advantage of optimization. After finding the global path, the mobile robot has to move toward targets without a collision. FLC(Fuzzy Logic Controller) is used for local path planning. FLC decides where and how faster the mobile robot moves. The validity of the study that searches the shortest global path using GA in multi targets and moves to targets without a collision using FLC, is verified by simulations.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2009.05a
• /
• pp.199-202
• /
• 2009

The optimal path on real road network has been changed by traffic flow of roads frequently. Therefore a path finding system to find the optimal path on real network should consider traffic flow of roads that is changed on real time. The most of existing path finding methods do not consider traffic flow of roads and do not also perform efficiently if they use traffic information. In this paper, we propose an abstraction method of real road network based on the Terminal Based Navigation System (TBNS) with technique such as TPEG. TBNS can be able to provides quality of path better than before as using traffic information that is transferred by TPEG. The proposed method is to abstract real network as simple graph in order to use traffic information. It is composed boundary nodes based on real nodes, all boundary nodes that have the same of connection are merged together. The result of path finding on an abstract graph diminishes the search space.

• Journal of the Korean Operations Research and Management Science Society
• /
• v.14 no.1
• /
• pp.72-79
• /
• 1989

In this paper we consider the problem of finding an optimal straight line path of moving facility which interacts with a set of existing facilities fixed within a given rectangular area. We present a simple algorithm for rectilinear metric which greatly improves the pervious method and also propose algorithms for Euclidean and squared Euclidean distances.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2001.04a
• /
• pp.398-401
• /
• 2001

This paper presents rough cutting pat고 drilling. This method has differences from conventional method which uses boundary curve by intersecting object to machine and each cutting plane. Die-cavity shape is drilled in z-map, we select various tool and remove much material in the short time. as a result, this method raise productivity. The major challenges in die-cavity pocketing include : 1)finding an inscribed circle for removing material of unmachined regions, 2) selecting optimal tool and efficiently arranging tool, 3) generating offset surface of shape, 4) determining machined width according to the selected tool, 5) detecting and removing unmachined regions, and 6) linking PJE(path-joining element). Conventional machining method calling contour-map is compared with drilling method using Z-map, for finding efficiency in the view of productivity.

• Proceedings of the IEEK Conference
• /
• 2006.06a
• /
• pp.1007-1008
• /
• 2006

This paper presents a optimal path search of mobile robot using energy efficiency. Proposed method has two goals that determining the velocity of mobile robot and finding the optimal path. We model the relationship of motors' speed and power consumption with quadratic polynomials. In order to verify the effectiveness of the proposed method, we performed simulations on the energy consumption of different paths.

• Proceedings of the KIEE Conference
• /
• 1996.07b
• /
• pp.1389-1391
• /
• 1996

In this paper, we applies two methods - Genetic Algorithm(GA) and $A^*$ Algorithm - to find the optimal path in route guidance system. Under the assumption that the traveling costs of each link are given, the task to find the optimal path becomes very complicated problem if the number of nodes or links increase. Two well-known algorithms are modified to resolve the problem and the preliminary demonstration show both optimistic result and needs to improvement.