NDLI: A new meta-heuristic ebb-tide-fish-inspired algorithm for traffic navigation

Content Provider	Springer Nature Link
Author	Meng, Zhenyu Pan, Jeng Shyang Alelaiwi, Abdulhameed
Copyright Year	2015
Abstract	More and more bio-inspired or meta-heuristic algorithms have been proposed to tackle the tough optimization problems. They all aim for tolerable velocity of convergence, a better precision, robustness, and performance. In this paper, we proposed a new algorithm, ebb tide fish algorithm (ETFA), which mainly focus on using simple but useful update scheme to evolve different solutions to achieve the global optima in the related tough optimization problem rather than PSO-like velocity parameter to achieve diversity at the expenses of slow convergence rate. The proposed ETFA achieves intensification and diversification in a new way. First, a flag is used to demonstrate the search status of each particle candidate. Second, the single search mode and population search mode tackle the intensification and diversification for tough optimization problem respectively. We also compare the proposed algorithm with other existing algorithms, including bat algorithm, cat swarm optimization, harmony search algorithm and particle swarm optimization. Simulation results demonstrate that the proposed ebb tide fish algorithm not only obtains a better precision but also gets a better convergence rate. Finally, the proposed algorithm is used in the application of vehicle route optimization in Intelligent Transportation Systems (ITS). Experiment results show that the proposed scheme also can be well performed for vehicle navigation with a better performance of the reduction of gasoline consumption than the shortest path algorithm (Dijkstra Algorithm) and A* algorithm.
Starting Page	403
Ending Page	415
Page Count	13
File Format	PDF
ISSN	10184864
Journal	Telecommunication Systems
Volume Number	62
Issue Number	2
e-ISSN	15729451
Language	English
Publisher	Springer US
Publisher Date	2015-09-10
Publisher Place	New York
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Benchmark function Bio-inspired algorithm Ebb tide fish algorithm Gasoline consumption Meta-heuristic optimization Vehicle navigation IT in Business Computer Communication Networks Artificial Intelligence (incl. Robotics) Probability Theory and Stochastic Processes
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering

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