• Title/Summary/Keyword: Optimal Route Algorithm

Search Result 190, Processing Time 0.02 seconds

Reviews of Bus Transit Route Network Design Problem (버스 노선망 설계 문제(BTRNDP)의 고찰)

  • Han, Jong-Hak;Lee, Seung-Jae;Lim, Seong-Su;Kim, Jong-Hyung
    • Journal of Korean Society of Transportation
    • /
    • v.23 no.3 s.81
    • /
    • pp.35-47
    • /
    • 2005
  • This paper is to review a literature concerning Bus Transit Route Network Design(BTRNDP), to describe a future study direction for a systematic application for the BTRNDP. Since a bus transit uses a fixed route, schedule, stop, therefore an approach methodology is different from that of auto network design problem. An approach methodology for BTRNDP is classified by 8 categories: manual & guideline, market analysis, system analytic model. heuristic model. hybrid model. experienced-based model. simulation-based model. mathematical optimization model. In most previous BTRNDP, objective function is to minimize user and operator costs, and constraints on the total operator cost, fleet size and service frequency are common to several previous approach. Transit trip assignment mostly use multi-path trip assignment. Since the search for optimal solution from a large search space of BTRNDP made up by all possible solutions, the mixed combinatorial problem are usually NP-hard. Therefore, previous researches for the BTRNDP use a sequential design process, which is composed of several design steps as follows: the generation of a candidate route set, the route analysis and evaluation process, the selection process of a optimal route set Future study will focus on a development of detailed OD trip table based on bus stop, systematic transit route network evaluation model. updated transit trip assignment technique and advanced solution search algorithm for BTRNDP.

Deep learning based optimal evacuation route guidance system in case of structure fire disaster (딥러닝 기반의 구조물 화재 재난 시 최적 대피로 안내 시스템)

  • Lim, Jae Don;Kim, Jung Jip;Hong, Dueui;Jung, Hoekyung
    • Journal of the Korea Institute of Information and Communication Engineering
    • /
    • v.23 no.11
    • /
    • pp.1371-1376
    • /
    • 2019
  • In case of fire in a structure, it is difficult to suppress fire because it can not accurately grasp the location of fire in case of fire. In this paper, we propose a system algorithm that can guide the optimal evacuation route in case of deep learning-based (RNN) structure disaster. The present invention provides a service to transmit data detected by sensors to a server in real time by using installed sensor, to transmit and analyze information such as temperature, heat, smoke, toxic gas around the sensor, to identify the safest moving path within a set threshold, to transmit information to LED guide lights and direction indicators in a structure in real time to avoid risk factors. This is because the information of temperature, heat, smoke, and toxic gas in each area of the structure can be grasped, and it is considered that the optimal evacuation route can be guided in case of structure disaster.

Insect-Inspired Algorithm for Zone Radius Determination of Ad-hoc Networks (곤충 행동 양식 기반의 애드 혹 네트워크를 위한 존 반경 결정 알고리즘)

  • Lee, Hea-Min;Kim, Dong-Seong
    • Journal of Institute of Control, Robotics and Systems
    • /
    • v.20 no.10
    • /
    • pp.1079-1083
    • /
    • 2014
  • In this paper, a new zone radius determination algorithm is proposed for a nature-inspired routing protocol that emulates the foraging behavior of bees based on their ability to find an optimal route from nectar sites. Instead of changing the radius of nodes one-hop by one-hop, the proposed algorithm alters the radius of nodes as gaps of another radius and adapt quickly to network conditions. The simulation results show that the proposed algorithm has higher efficiency compared with existing studies in an aspect of computational complexity and end-to-end delay.

A Study on the Real-time Optimization Technique for a Train Velocity Profile (실시간 열차 속도 프로파일 최적화 기법에 관한 연구)

  • Kim, Moosun;Kim, Jungtai;Park, Chul-Hong
    • Journal of the Korea Academia-Industrial cooperation Society
    • /
    • v.17 no.8
    • /
    • pp.344-351
    • /
    • 2016
  • In the point of view of a train operator, the main concern with a train operation is not only to maintain a time schedule, but also to decrease the energy consumption as much as possible. Generally for a manual drive, a train conductor controls the train acceleration and deceleration by controlling the notches not to exceed the regulation velocity by considering the given maximum velocity profile for an operation route. For this case, the guideline for a conductor is needed to choose the proper notches by applying the notch optimization so as to drive at the regulation velocity and minimize energy consumption simultaneously. In this paper, the real-time notch optimization plan is suggested using a genetic algorithm that optimizes the notches for the remaining route in real time when the event occurs that track information or regulation velocity profile of the remaining route changes during train operation as well as a normal operation situation. An energy saving effect and the convergence behavior of the optimal solution obtained was analyzed in a genetic algorithm.

AN OPTIMAL PARALLEL ALGORITHM FOR SOLVING ALL-PAIRS SHORTEST PATHS PROBLEM ON CIRCULAR-ARC GRAPHS

  • SAHA ANITA;PAL MADHUMANGAL;PAL TAPAN K.
    • Journal of applied mathematics & informatics
    • /
    • v.17 no.1_2_3
    • /
    • pp.1-23
    • /
    • 2005
  • The shortest-paths problem is a fundamental problem in graph theory and finds diverse applications in various fields. This is why shortest path algorithms have been designed more thoroughly than any other algorithm in graph theory. A large number of optimization problems are mathematically equivalent to the problem of finding shortest paths in a graph. The shortest-path between a pair of vertices is defined as the path with shortest length between the pair of vertices. The shortest path from one vertex to another often gives the best way to route a message between the vertices. This paper presents an $O(n^2)$ time sequential algorithm and an $O(n^2/p+logn)$ time parallel algorithm on EREW PRAM model for solving all pairs shortest paths problem on circular-arc graphs, where p and n represent respectively the number of processors and the number of vertices of the circular-arc graph.

Analysis of Infiltration Route using Optimal Path Finding Methods and Geospatial Information (지형공간정보 및 최적탐색기법을 이용한 최적침투경로 분석)

  • Bang, Soo Nam;Heo, Joon;Sohn, Hong Gyoo;Lee, Yong Woong
    • KSCE Journal of Civil and Environmental Engineering Research
    • /
    • v.26 no.1D
    • /
    • pp.195-202
    • /
    • 2006
  • The infiltration route analysis is a military application using geospatial information technology. The result of the analysis would present vulnerable routes for potential enemy infiltration. In order to find the susceptible routes, optimal path search algorithms (Dijkstra's and $A^*$) were used to minimize the cost function, summation of detection probability. The cost function was produced by capability of TOD (Thermal Observation Device), results of viewshed analysis using DEM (Digital Elevation Model) and two related geospatial information coverages (obstacle and vegetation) extracted from VITD (Vector product Interim Terrain Data). With respect to 50m by 50m cells, the individual cost was computed and recorded, and then the optimal infiltration routes was found while minimizing summation of the costs on the routes. The proposed algorithm was experimented in Daejeon region in South Korea. The test results show that Dijkstra's and $A^*$ algorithms do not present significant differences, but A* algorithm shows a better efficiency. This application can be used for both infiltration and surveillance. Using simulation of moving TOD, the most vulnerable routes can be detected for infiltration purpose. On the other hands, it can be inversely used for selection of the best locations of TOD. This is an example of powerful geospatial solution for military application.

3 Dimensional Augmented Reality Flight for Drones

  • Park, JunMan;Kang, KiBeom;Jwa, JeongWoo;Won, JoongHie
    • International Journal of Internet, Broadcasting and Communication
    • /
    • v.10 no.2
    • /
    • pp.13-18
    • /
    • 2018
  • Drones are controlled by the remote pilot from the ground stations using the radio control or autonomously following the pre-programmed flight plans. In this paper, we develop a method and an optimal path search system for providing 3D augmented reality flight (ARF) images for safe and efficient flight control of drones. The developed system consisted of the drone, the ground station and user terminals, and the optimal path search server. We use the Dijkstra algorithm to find the optimal path considering the drone information, flight information, environmental information, and flight mission. We generate a 3D augmented reality flight (ARF) image overlaid with the path information as well as the drone information and the flight information on the flight image received from the drone. The ARF image for adjusting the drone is generated by overlaying route information, drone information, flight information, and the like on the image captured by the drone.

A Study on the efficient AODV Routing Algorithm using Cross-Layer Design (크로스레이어 디자인을 이용한 효율적인 AODV 알고리즘에 관한 연구)

  • Nam, Ho-Seok;Lee, Tae-Hoon;Do, Jae-Hwan;Kim, Jun-Nyun
    • The Journal of Korean Institute of Communications and Information Sciences
    • /
    • v.33 no.11B
    • /
    • pp.981-988
    • /
    • 2008
  • In this paper, the efficient AODV routing algorithm in MANET is proposed. Because transmission channel has a high error rate and loss in MANET, the number of hops can't be regarded as an absolute network metric. After measuring FER periodically at the data link layer using cross-layer design, the scheme that every node forwards the weight of link status in the reserved field of AODV protocol is used. In order to find the efficient route, we design AODV to be able to select an optimal route that has a good channel status by evaluating the sum of weight. The proposed AODV improves throughput, routing overhead and average end-to-end delay in comparison with the generic AODV.

A Link-Label Based Node-to-Link Optimal Path Algorithm Considering Non Additive Path Cost (비가산성 경로비용을 반영한 링크표지기반 Node-to-Link 최적경로탐색)

  • Lee, Mee Young;Nam, Doohee
    • 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.

New Mathematical Model and Parallel Hybrid Genetic Algorithm for the Optimal Assignment of Strike packages to Targets (공격편대군-표적 최적 할당을 위한 수리모형 및 병렬 하이브리드 유전자 알고리즘)

  • Kim, Heungseob;Cho, Yongnam
    • Journal of the Korea Institute of Military Science and Technology
    • /
    • v.20 no.4
    • /
    • pp.566-578
    • /
    • 2017
  • For optimizing the operation plan when strike packages attack multiple targets, this article suggests a new mathematical model and a parallel hybrid genetic algorithm (PHGA) as a solution methodology. In the model, a package can assault multiple targets on a sortie and permitted the use of mixed munitions for a target. Furthermore, because the survival probability of a package depends on a flight route, it is formulated as a mixed integer programming which is synthesized the models for vehicle routing and weapon-target assignment. The hybrid strategy of the solution method (PHGA) is also implemented by the separation of functions of a GA and an exact solution method using ILOG CPLEX. The GA searches the flight routes of packages, and CPLEX assigns the munitions of a package to the targets on its way. The parallelism enhances the likelihood seeking the optimal solution via the collaboration among the HGAs.