A novel optimal route planning algorithm for searching on the sea

2021 ◽  
pp. 1-19
Author(s):  
Y. Yang ◽  
Y. Mao ◽  
R. Xie ◽  
Y. Hu ◽  
Y. Nan
Keyword(s):  
Optimal Algorithm ◽  
Route Planning ◽  
Search And Rescue ◽  
Search Rate ◽  
Planning Problem ◽  
Optimal Route ◽  
Planning Algorithm ◽  
Discrete Programming ◽  
Maritime Search And Rescue ◽  
National Emergency

ABSTRACT Emergency search and rescue on the sea is an important part of national emergency response for marine perils. Optimal route planning for maritime search and rescue is the key capability to reduce the searching time, improve the rescue efficiency, as well as guarantee the rescue target’s safety of life and property. The main scope of the searching route planning is to optimise the searching time and voyage within the constraints of missing search rate and duplicate search rate. This paper proposes an optimal algorithm for searching routes of large amphibious aircraft corresponding to its flight characteristics and sea rescue capability. This algorithm transforms the search route planning problem into a discrete programming problem and applies the route traceback indexes to satisfy the duplicate search rate and missing search rate.

scholarly journals Semantic-Aware Top-k Multirequest Optimal Route

Complexity ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-15
Author(s):  
Shuang Wang ◽  
Yingchun Xu ◽  
Yinzhe Wang ◽  
Hezhi Liu ◽  
Qiaoqiao Zhang ◽  
...  
Keyword(s):  
Semantic Similarity ◽  
Route Planning ◽  
Location Based Services ◽  
Optimal Route ◽  
Wide Range ◽  
Potential Applications ◽  
Planning Algorithm ◽  
Keyword Searching ◽  
Path Queries ◽  
Indexing Technique

In recent years, research on location-based services has received a lot of interest, in both industry and academic aspects, due to a wide range of potential applications. Among them, one of the active topic areas is the route planning on a point-of-interest (POI) network. We study the top-k optimal routes querying on large, general graphs where the edge weights may not satisfy the triangle inequality. The query strives to find the top-k optimal routes from a given source, which must visit a number of vertices with all the services that the user needs. Existing POI query methods mainly focus on the textual similarities and ignore the semantic understanding of keywords in spatial objects and queries. To address this problem, this paper studies the semantic similarity of POI keyword searching in the route. Another problem is that most of the previous studies consider that a POI belongs to a category, and they do not consider that a POI may provide various kinds of services even in the same category. So, we propose a novel top-k optimal route planning algorithm based on semantic perception (KOR-SP). In KOR-SP, we define a dominance relationship between two partially explored routes which leads to a smaller searching space and consider the semantic similarity of keywords and the number of single POI’s services. We use an efficient label indexing technique for the shortest path queries to further improve efficiency. Finally, we perform an extensive experimental evaluation on multiple real-world graphs to demonstrate that the proposed methods deliver excellent performance.

scholarly journals GRASP-Tabu Search Algorithms for the Route Planning Problem in Spatial Crowdsourcing

2022 ◽  
Vol 13 (1) ◽  
pp. 0-0
Keyword(s):  
Route Planning ◽  
Search Algorithms ◽  
Spatial Task ◽  
Planning Problem ◽  
Limited Time ◽  
Computational Results ◽  
Optimal Route ◽  
Spatial Crowdsourcing ◽  
Spatial Tasks ◽  
Benchmark Instances

With the speedy progress of mobile devices, a lot of commercial enterprises have exploited crowdsourcing as a useful approach to gather information to develop their services. Thus, spatial crowdsourcing has appeared as a new platform in e-commerce and which implies procedures of requesters and workers. A requester submits spatial tasks request to the workers who choose and achieve them during a limited time. Thereafter, the requester pays only the worker for the well accomplished the task. In spatial crowdsourcing, each worker is required to physically move to the place to accomplish the spatial task and each task is linked with location and time. The objective of this article is to find an optimal route to the worker through maximizing her rewards with respecting some constraint, using an approach based on GRASP with Tabu. The proposed algorithm is used in the literature for benchmark instances. Computational results indicate that the proposed and the developed algorithm is competitive with other solution approaches.

Optimal Route Planning Algorithm Based on Real Traffic Network

2005 ◽  
Author(s):  
Nae-Seung Kang ◽  
Byung-Sung Kim ◽  
Ho-Joong Kim
Keyword(s):  
Route Planning ◽  
Traffic Network ◽  
Optimal Route ◽  
Planning Algorithm ◽  
Real Traffic

Multi-Helicopter Search and Rescue Route Planning Based on Strategy Optimization Algorithm

2018 ◽  
Vol 33 (01) ◽  
pp. 1950002 ◽  
Author(s):  
Quan Shao ◽  
Chenchen Xu ◽  
Yan Zhu
Keyword(s):  
Ant Colony Algorithm ◽  
Route Planning ◽  
Behavioral Model ◽  
Search And Rescue ◽  
Planning Model ◽  
Cooperative Search ◽  
Rescue Operation ◽  
Algorithm Efficiency ◽  
Planning Algorithm ◽  
Efficient Route

This paper attempts to develop an efficient route planning algorithm to guide the operations of the multi-helicopter search and rescue in emergency. Route planning model of multi-helicopter cooperative search and rescue activity was established first, based on preference ordering of search and rescue objectives, as well as behavioral model of rescue helicopter and on-board detector. Given the route planning model, a multi-helicopter search and rescue route planning general algorithm was developed. The operation mechanism of ant colony algorithm was improved by introducing cooperative modes and the pheromone updating mechanism into existing methods. Furthermore, two cooperative search and rescue modes were studied: one is Overall Cooperative Search and Rescue Mode (OCSARM), in which many ants search and rescue the same region all together; the other is Blocking Cooperative Search and Rescue Mode (BCSARM), which partitions the region into small blocks and appoints helicopter with corresponding performance capabilities. Simulated experiments were developed to test the operability of proposed multi-helicopter search and rescue route planning algorithm. The comparison with existing algorithm shows that the algorithm proposed in this paper reduces computational complexity and evidently enhances algorithm efficiency. Results also indicate that this algorithm not only has the capability of comparing efficiency of two search and rescue modes in different mission requirements but also helps select search and rescue modes before rescue operation.

Time optimal route planning algorithm of LBS online navigation

2011 ◽  
Author(s):  
Yong Li ◽  
Shitai Bao ◽  
Kui Su ◽  
Qiushui Fang ◽  
Jingfeng Yang
Keyword(s):  
Route Planning ◽  
Optimal Route ◽  
Time Optimal ◽  
Planning Algorithm

scholarly journals Flexible Route Planning for Sightseeing with Fuzzy Random and Fatigue-Dependent Satisfactions

2014 ◽  
Vol 18 (2) ◽  
pp. 190-196 ◽  
Author(s):  
Takashi Hasuike ◽  
◽  
Hideki Katagiri ◽  
Hiroe Tsubaki ◽  
Hiroshi Tsuda ◽  
...  
Keyword(s):  
Fuzzy Numbers ◽  
Random Variables ◽  
Route Planning ◽  
Planning Problem ◽  
Optimal Route ◽  
Travel Times ◽  
Fuzzy Random Variables ◽  
Order Relations ◽  
Proposed Model ◽  
Fuzzy Random

This paper proposes a flexible route planning problem for sightseeing with fuzzy random variables for travel times and satisfaction with activities under general sightseeing constraints. Travel time between sightseeing sites and satisfactions with activities depend on weather and climate conditions, and on traveler fatigue, so both fuzzy random variables for travel times and satisfactions and traveler fatigue-dependence are introduced. Tourists are likely to plan favored without drastically changing from the optimal route under usual conditions such as fine weather that suddenly changes for the worse. A route planning problem is proposed to obtain a favorite route similar to the optimal route under usual conditions. Trapezoidal fuzzy numbers and order relations are introduced as a basic case of fuzzy numbers. From order relations, the proposed model is transformed into an extended model of network optimization problems. A numerical example is used to compare the proposed model to standard route planning problems in sightseeing.

scholarly journals Optimal search and rescue route design using an improved ant colony optimization

2020 ◽  
Vol 49 (3) ◽  
pp. 438-447
Author(s):  
Haichuan ZHANG ◽  
Jingwen SUN ◽  
Baolong YANG ◽  
Yinghu SHI ◽  
Zhanying LI
Keyword(s):  
Ant Colony Algorithm ◽  
Search And Rescue ◽  
Ant Colony ◽  
Actual Situation ◽  
Optimal Solutions ◽  
Optimal Route ◽  
Pheromone Concentration ◽  
Route Design ◽  
Simulation Results ◽  
Maritime Search And Rescue

In this paper, an improved ant colony algorithm is proposed for the route design of maritime emergency search and rescue. To solve the problem that the ant colony algorithm is easy to fall into local optimal solutions in the process of searching, the pheromone concentration updating strategy of the original ant colony algorithm is provided. According to the actual situation of maritime search and rescue, the path weight based on the time of falling into the water is introduced into the algorithm to obtain the optimal route. The simulation results show that the improved algorithm can be used for route design, and obtain the optimal route suitable for sea search and rescue.

scholarly journals The Gradational Route Planning for Aircraft Stealth Penetration Based on Genetic Algorithm and Sparse A-Star Algorithm

2018 ◽  
Vol 151 ◽  
pp. 04001 ◽  
Author(s):  
Li Maoquan ◽  
Zhang Yunfei ◽  
Li Shihao
Keyword(s):  
Genetic Algorithm ◽  
Detection Probability ◽  
Optimal Path ◽  
Route Planning ◽  
Goal Function ◽  
Optimal Route ◽  
Optimal Path Planning ◽  
Planning Algorithm ◽  
Global Optimal ◽  
The Cost

It is established for a gradational route planning algorithm which includes two layers. The first layer makes use of genetic algorithm to obtain the global optimal path by its global optimal characteristics. The second layer makes use of A* algorithm to obtain the local optimal path by its dynamic characteristic. When flying along the global optimal path, locating the new threat and confirming its performance, the aircraft can plan the local optimal path timely by A* algorithm. It is constructed for the cost function with two goals of the range and the average detection probability, which is used as the goal function for optimal path planning. Two paths that obtained from two optimal methods are merged to construct the optimal route comprehensively considering the threats and range. The simulation result shows that the cost of new optimal route is lower than the original optimal path obtained only by the genetic algorithm.It revealed that our algorithm could obtain an optimal path when a new radar threas occured.

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