The Kalman Filter Cuckoo Search Algorithm to Solve the TSP Problem

Juan Li; Ting Zhang

doi:10.4028/www.scientific.net/AMM.733.918

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vol. 733The Kalman Filter Cuckoo Search Algorithm to Solve...

The Kalman Filter Cuckoo Search Algorithm to Solve the TSP Problem

Abstract:

TSP problem optimization is a combinatorial optimization model studied which is NP hard, and it has been solved by a lot of algorithms. A new improved cuckoo optimization algorithm (KF-CS) has been put forward to solve the routing optimization problem of logistics distribution vehicle. Kalman Filter Cuckoo search (KF-CS) is a new intelligent algorithm which used to estimate the state of a stochastic phenomenon which has Gaussian distribution. The problem of travelling salesman was experimented. To demonstrate the effectiveness and efficiency of the proposed algorithm, the benchmark problems from TSPLIB were tested and compared with PSO, DE, ACO and standard CS. The results showed that the KF-CS algorithm achieved shorter distances in all cases within fewer generations, and it has obvious effects to find the optimal solution frequency and time.

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Periodical:

Applied Mechanics and Materials (Volume 733)

Pages:

918-921

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.733.918

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Online since:

February 2015

Authors:

Juan Li*, Ting Zhang

Keywords:

Cuckoo Search Algorithm, Kalman Filter, TSP Optimum Problem

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