Simulation of identifying shortest path walkway using particle swarm optimization (PSO)
The purpose of this research is to present the development of the system of Simulation of Identifying Shortest Path Walkway using Particle Swarm Optimization(PSO). This application system is use to solve the shortest path problem in the simulated environment.The suggested simulation environment is a...
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2012
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Online Access: | http://umpir.ump.edu.my/id/eprint/4440/1/CD6564_YONG_KAE_SHIN.pdf http://umpir.ump.edu.my/id/eprint/4440/ |
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my.ump.umpir.44402021-07-16T05:11:05Z http://umpir.ump.edu.my/id/eprint/4440/ Simulation of identifying shortest path walkway using particle swarm optimization (PSO) Kae Shin, Yong QA Mathematics The purpose of this research is to present the development of the system of Simulation of Identifying Shortest Path Walkway using Particle Swarm Optimization(PSO). This application system is use to solve the shortest path problem in the simulated environment.The suggested simulation environment is a restaurant.In the real world restaurant, if the waiter unable to deliver the food within short period of time,this may reduce the customer satisfaction and downgrade the work performance.This will not only happen in the restaurant,since people nowadays prefer the effective services. Therefore, this project is develop to find the shortest path which means to find a path with minimum distance between two locations by apply the algorithm of Particle Swarm Optimization technique.This system is expected to solve the shortest path and identify the optimal path.Due to this,it is tend to reduce the time consume in specific situation with the determining of shortest path. The development of this system could bring convenience and effectiveness for the work in progress. 2012-06 Undergraduates Project Papers NonPeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/4440/1/CD6564_YONG_KAE_SHIN.pdf Kae Shin, Yong (2012) Simulation of identifying shortest path walkway using particle swarm optimization (PSO). Faculty of Computer System & Software Engineering, Universiti Malaysia Pahang. |
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QA Mathematics Kae Shin, Yong Simulation of identifying shortest path walkway using particle swarm optimization (PSO) |
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The purpose of this research is to present the development of the system of Simulation of Identifying Shortest Path Walkway using Particle Swarm Optimization(PSO). This application system is use to solve the shortest path problem in the simulated environment.The suggested simulation environment is a restaurant.In the real world restaurant, if the waiter unable to deliver the food within short period of time,this may reduce the customer satisfaction and downgrade the work performance.This will not only happen in the restaurant,since people nowadays prefer the effective services. Therefore, this project is develop to find the shortest path which means to find a path with minimum distance between two locations by apply the algorithm of Particle Swarm Optimization technique.This system is expected to solve the shortest path and identify the optimal path.Due to this,it is tend to reduce the time consume in specific situation with the determining of shortest path. The development of this system could bring convenience and effectiveness for the work in progress. |
format |
Undergraduates Project Papers |
author |
Kae Shin, Yong |
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Kae Shin, Yong |
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Kae Shin, Yong |
title |
Simulation of identifying shortest path walkway using particle swarm optimization (PSO) |
title_short |
Simulation of identifying shortest path walkway using particle swarm optimization (PSO) |
title_full |
Simulation of identifying shortest path walkway using particle swarm optimization (PSO) |
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Simulation of identifying shortest path walkway using particle swarm optimization (PSO) |
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Simulation of identifying shortest path walkway using particle swarm optimization (PSO) |
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simulation of identifying shortest path walkway using particle swarm optimization (pso) |
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2012 |
url |
http://umpir.ump.edu.my/id/eprint/4440/1/CD6564_YONG_KAE_SHIN.pdf http://umpir.ump.edu.my/id/eprint/4440/ |
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13.211869 |