Application Research on Optimal Path Based on Genetic Algorithm

2010 ◽  
Vol 4 (8) ◽  
pp. 199-202 ◽  
Author(s):  
Lilin FAN ◽  
Huili MENG
Keyword(s):  
Genetic Algorithm ◽  
Optimal Path ◽  
Application Research

An Optimal Routing Algorithm for Internet of Things Enabling Technologies

2017 ◽  
Vol 4 (3) ◽  
pp. 1-16 ◽  
Author(s):  
Amol V. Dhumane ◽  
Rajesh S. Prasad ◽  
Jayashree R. Prasad
Keyword(s):  
Genetic Algorithm ◽  
Internet Of Things ◽  
Energy Cost ◽  
High Reliability ◽  
Routing Algorithm ◽  
Optimal Path ◽  
Cluster Head ◽  
Sensor Nodes ◽  
Trust Level ◽  
Enabling Technologies

In Internet of things and its relevant technologies the routing of data plays one of the major roles. In this paper, a routing algorithm is presented for the networks consisting of smart objects, so that the Internet of Things and its enabling technologies can provide high reliability while the transmitting the data. The proposed technique executes in two stages. In first stage, the sensor nodes are clustered and an optimal cluster head is selected by using k-means clustering algorithm. The clustering is performed based on energy of sensor nodes. Then the energy cost of the cluster head and the trust level of the sensor nodes are determined. At second stage, an optimal path will be selected by using the Genetic Algorithm (GA). The genetic algorithm is based on the energy cost at cluster head, trust level at sensor nodes and path length. The resultant optimal path provides high reliability, better speed and more lifetimes.

Path planning of a mobile robot using genetic heuristics

Robotica ◽  
1998 ◽  
Vol 16 (5) ◽  
pp. 575-588 ◽  
Author(s):  
Andreas C. Nearchou
Keyword(s):  
Genetic Algorithm ◽  
Path Planning ◽  
Mobile Robot ◽  
Optimal Path ◽  
Hill Climbing ◽  
Planning Problem ◽  
Well Performance ◽  
Simulation Results ◽  
Task Oriented ◽  
Path Planning Problem

A genetic algorithm for the path planning problem of a mobile robot which is moving and picking up loads on its way is presented. Assuming a findpath problem in a graph, the proposed algorithm determines a near-optimal path solution using a bit-string encoding of selected graph vertices. Several simulation results of specific task-oriented variants of the basic path planning problem using the proposed genetic algorithm are provided. The results obtained are compared with ones yielded by hill-climbing and simulated annealing techniques, showing a higher or at least equally well performance for the genetic algorithm.

scholarly journals Research on the Food Logistic Optimal Path Planning Method of Improving the Genetic Algorithm

2016 ◽  
Vol 11 (4) ◽  
pp. 269-273
Author(s):  
Li Si ◽  
Wang Yuan ◽  
Li Xinzhong ◽  
Liu Shenyang ◽  
Li Zhen
Keyword(s):  
Genetic Algorithm ◽  
Path Planning ◽  
Optimal Path ◽  
Planning Method ◽  
Optimal Path Planning

Optimal path planning and execution for mobile robots using genetic algorithm and adaptive fuzzy-logic control

2017 ◽  
Vol 89 ◽  
pp. 95-109 ◽  
Author(s):  
Azzeddine Bakdi ◽  
Abdelfetah Hentout ◽  
Hakim Boutami ◽  
Abderraouf Maoudj ◽  
Ouarda Hachour ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Fuzzy Logic ◽  
Path Planning ◽  
Mobile Robots ◽  
Fuzzy Logic Control ◽  
Optimal Path ◽  
Adaptive Fuzzy ◽  
Optimal Path Planning ◽  
Logic Control ◽  
Adaptive Fuzzy Logic
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