• Title/Summary/Keyword: optimal route search algorithm

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Android Application for Connecting Cycling Routes on Strava Segments

  • Mulasastra, Intiraporn;Kao-ian, Wichpong
    • Journal of information and communication convergence engineering
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    • v.17 no.2
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    • pp.142-148
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    • 2019
  • Relatively few countries provide separate bicycle lanes for cyclists. Hence, tools for suggesting cycling routes are essential for a safe and pleasant cycling experience. This study aims to develop a mobile application to build cycling routes based on user preferences, specifically location, search radius, ride distance, and number of optimal routes. Our application calls the Strava API to retrieve Strava cycling segments crowdsourced from the cycling community. Then, it creates a graph consisting of the start and end points of these segments. Beginning from a user-specified location, the depth-first search algorithm (DFS) is applied to find routes that conform to the user's preferences. Next, a set of optimal routes is obtained by computing a trade-off ratio for every discovered route. This ratio is calculated from the lengths of all segments and the lengths of all connecting paths. The connected routes can be displayed on a map on an Android device or exported as a GPX file to a bike computer. Future work must be performed to improve the design of the user interface and user experience.

Railway Timetable Considering Optimal Path Finding Method in Rail Network (Focused on Revenue Allocation) (열차스케줄을 고려한 도시철도 이용객의 통행행태 추정 (수입금 정산사례를 중심으로))

  • Lee, Chang-Hun;Shin, Seong-Il;Kim, Si-Gon
    • Journal of the Korean Society for Railway
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    • v.18 no.2
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    • pp.149-156
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    • 2015
  • It is necessary to determine real path for urban railway users in order to allocate revenues between urban railway organizations. Out of several algorithms used to determine optimal routes, the k-path algorithm based on link-label has been utilized. However, this k-path algorithm has certain flaws. For example, optimal route can change depending on the travel and walking time, transfer penalty, and so on. Also, this algorithm cannot take into account the characteristics of users, who prefer express train to normal trains. In this paper, an algorithm is proposed to determine one single optimal route based on the traffic card data. This method also can search for an optimal path in conjunction with the railway timetable.

3 Dimensional Augmented Reality Flight for Drones

  • Park, JunMan;Kang, KiBeom;Jwa, JeongWoo;Won, JoongHie
    • International Journal of Internet, Broadcasting and Communication
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    • v.10 no.2
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    • pp.13-18
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    • 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.

Comparison and Analysis of Information Exchange Distributed Algorithm Performance Based on a Circular-Based Ship Collision Avoidance Model (원형 기반 선박 충돌 피항 모델에 기반한 정보 교환 분산알고리즘 성능 비교 분석)

  • Donggyun Kim
    • Journal of Navigation and Port Research
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    • v.47 no.6
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    • pp.401-409
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    • 2023
  • This study compared and analyzed the performance of a distributed area search algorithm and a distributed probability search algorithm based on information exchange between ships. The distributed algorithm is a method that can search for an optimal avoidance route based on information exchange between ships. In the distributed area search algorithm, only a ship with the maximum cost reduction among neighboring ships has priority, so the next expected location can be changed. The distributed stochastic search algorithm allows a non-optimal value to be searched with a certain probability so that a new value can be searched. A circular-based ship collision avoidance model was used for the ship-to-ship collision avoidance experiment. The experimental method simulated the distributed area search algorithm and the distributed stochastic search algorithm while increasing the number of ships from 2 to 50 that were the same distance from the center of the circle. The calculation time required for each algorithm, sailing distance, and number of message exchanges were compared and analyzed. As a result of the experiment, the DSSA(Distributed Stochastic Search Algorithm) recorded a 25%calculation time, 88% navigation distance, and 84% of number of message exchange rate compared to DLSA.

Development of a Method for Partial Searching Technique for Optimal Path Finding in the Long Journey Condition (장거리 최적경로탐색을 위한 부분탐색기법 연구)

  • Bae, Sanghoon
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.26 no.3D
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    • pp.361-366
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    • 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.

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
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    • v.23 no.3 s.81
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    • pp.35-47
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    • 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.

A Method to determine Search Space of Hierarchical Path Algorithm for Finding Optimal Path (최적 경로 탐색을 위한 계층 경로 알고리즘의 탐색 영역 결정 기법)

  • Lee, Hyoun-Sup;Kim, Jin-Deog
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2007.10a
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    • pp.565-569
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    • 2007
  • To find optimal path is killer application in the telematics system. The shortest path of conventional system, however, isn't always optimal path. That is, the path with minimum travelling time could be defined as optimal path in the road networks. There are techniques and algorithms for finding optimal path. Hierarchical path algorithm categorizes road networks into major layer and minor layer so that the performance of operational time increases. The path searched is accurate as much as optimal path. At above 2 system, a method to allocate minor roads to major road region influences the performance extremely. This paper proposes methods to determine search space for selecting major roads in the hierarchical path algorithm. In addition, methods which apply the proposed methods to hierarchical route algorithm is presented.

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Exploring the Optimal Path to Adjacent Multiple Waypoints based on Harmony Search algorithms (하모니서치 알고리즘 기반 인접 다중 경유지 최적 경로 탐색 기법)

  • Yeji Tak;Seungmin Park
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2023.07a
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    • pp.689-691
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    • 2023
  • 본 논문에서는 시작 노드와 목적지 노드 까지의 최단경로를 중점으로 가장 인접한 경유지를 선택하고 경유지가 다수일 경우 하모니서치 알고리즘을 통해 최적의 경로를 탐색하는 기법을 제안한다. 본 논문의 기법은 기존의 사용자의 현 위치에서 인접한 경유지를 추천해주는 시스템과 달리 목적지까지의 경로 전체에서 가장 인접한경유지를 선택해준다는 차별점이 있다. 그렇게 선택된 경유지들은 하모니서치 알고리즘을 사용하여 최적의 경로를 제안한다. 본 논문의 기법은 최단경로의 이탈을 최소화한 경유지 선택으로 거리, 시간, 비용적 측면에서 효율적이며 길을 헤매서 생기는 불필요한 지연을 최소화할 수 있다. 자율주행, 비행기, 선박, 드론 등 최적 경로 이탈시 큰 손실을 안기거나 위험한 시스템에 적용시 큰 효과를 거둘 수 있다.

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Solving the Travelling Salesman Problem Using an Ant Colony System Algorithm

  • Zakir Hussain Ahmed;Majid Yousefikhoshbakht;Abdul Khader Jilani Saudagar;Shakir Khan
    • International Journal of Computer Science & Network Security
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    • v.23 no.2
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    • pp.55-64
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    • 2023
  • The travelling salesman problem (TSP) is an important combinatorial optimization problem that is used in several engineering science branches and has drawn interest to several researchers and scientists. In this problem, a salesman from an arbitrary node, called the warehouse, starts moving and returns to the warehouse after visiting n clients, given that each client is visited only once. The objective in this problem is to find the route with the least cost to the salesman. In this study, a meta-based ant colony system algorithm (ACSA) is suggested to find solution to the TSP that does not use local pheromone update. This algorithm uses the global pheromone update and new heuristic information. Further, pheromone evaporation coefficients are used in search space of the problem as diversification. This modification allows the algorithm to escape local optimization points as much as possible. In addition, 3-opt local search is used as an intensification mechanism for more quality. The effectiveness of the suggested algorithm is assessed on a several standard problem instances. The results show the power of the suggested algorithm which could find quality solutions with a small gap, between obtained solution and optimal solution, of 1%. Additionally, the results in contrast with other algorithms show the appropriate quality of competitiveness of our proposed ACSA.

A Comparison and Analysis of Ship Optimal Routing Scenarios considering Ocean Environment (해상환경을 고려한 선박항로의 최적화 시나리오 비교분석)

  • Park, Jinmo;Kim, Nakwan
    • Journal of the Society of Naval Architects of Korea
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    • v.51 no.2
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    • pp.99-106
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    • 2014
  • Weather routing of a ship provides an optimal route to the destination by using minimal time or fuel in a given sea condition. These days, weather routing came into a spotlight with soaring fuel price and the environmental regulations of IMO and several countries. This study presents three scenarios of voyaging strategies for a ship and compared them in terms of the fuel consumption. The first strategy fixes the speed of a ship as a constant value for entire sailing course, the second fixes the RPM of the ship as constant for entire course, and the third determines the RPMs of the ship for each segment of the course. For each strategy, a ship route is optimized by using the $A^*$ search method. Wind, ocean current and wave are considered as ocean environment factors when seeking the optimal routes. Based on 7000 TEU container ship's sea trial records, simulation has been conducted for three scenarios, and the most efficient routing scenario is determined in the view of fuel consumption.