Enhanced Genetic Algorithm Inspired Cuckoo Search (GACS) Algorithm for Combinatorial Optimization Travelling Salesman Problem
Keywords:
MLT, TSP, Genetic Algorithm, Cuckoo search, NP Hard problemAbstract
MLT finds potentially useful patterns in the data. Optimisation problems, either single-objective or multi-objective, are generally difficult to solve. The most famous example is probably the traveling salesman problem (TSP) in which a salesperson intends to visit a number of cities exactly once, and returning to its starting point, while minimizing the total distance traveled or the overall cost of the trip. TSP is one of the most widely studied problems in combinatorial optimization. It belongs to the class of NP-hard optimization problems, whose the computational complexity increases exponentially with the number of cities. It is often used for testing optimization algorithms. This paper proposed genetic algorithm based cuckoo search technique for TSP. Result significantly improves the performance of the TSP. The algorithm is implemented using MATLAB. Results seems to be promising when compared with the existing methods for the problem.
References
- Ms. Rinky Dwivedi, Japleen Kaur, Divya Dawra, Devanshi Rish1 and Manusmriti Nandal, “IMPLEMENTING AND ANALYSING FUZZY CONTROLLER WITH ACO ON TRAVELLING SALESMAN PROBLEM” Elsevier, 2014..
- Oloruntoyin Sefiu Taiwo, Olukehinde Olutosin Mayowa & Kolapo Bukola Ruka, “APPLICATION OF GENETIC ALGORITHM TO SOLVE TRAVELLING SALESMAN PROBLEM” International Journal of Advance Research, Volume 1, Issue 4, April 2013.
- Musa PEKER, Baha SEN, P_nar Yildiz KUMRU, “AN EFFICIENT SOLVING OF THE TRAVELING SALESMAN PROBLEM: THE ANT COLONY SYSTEM HAVING PARAMETERS OPTIMIZED BY THE TAGUCHI METHOD” Turkish Journal of Electrical Engineering & Computer Sciences, 2013.
- Marco Dorigo and Luca Maria Gambardella, “ANT COLONY SYSTEM: A COOPERATIVE LEARNING APPROACH TO THE TRAVELING SALESMAN PROBLEM “ IEEE Transactions on Evolutionary Computation, Vol.1, No.1, 1997.
- F.S.Gharehchopogh, I.Maleki, S.R.Khaze, “A NEW APPROACH IN DYNAMIC TRAVELING SALESMAN SOLUTION: A HYBRID OF ANT COLONY OPTIMIZATION AND DESCENDING GRADIENTS”, International Journal of Managing Public Sector Information and Communication Technologies (IJMPICT), Vol. 3, No. 2, pp. 1-9, December 2012.
- A. Toofani, “SOLVING ROUTING PROBLEM USING PARTICLE SWARM OPTIMIZATION”, International Journal of Computer Applications, Vol. 52, No.18, pp. 16-18, August 2012.
- M. H.Mehta, “HYBRID GENETIC ALGORITHM WITH PSO EFFECT FOR COMBINATORIAL OPTIMIZATION PROBLEMS”, International Journal of Advanced Computer Research, Vol. 2, No. 4, pp. 300-305, December 2012.
- I. Maleki, S. R.Khaze, F. S.Gharehchopogh, “A NEW SOLUTION FOR DYNAMIC TRAVELLING SALESMAN PROBLEM WITH HYBRID ANT COLONY OPTIMIZATION ALGORITHM AND CHAOS THEORY”, International Journal of Advanced Research in Computer Science (IJARCS), Vol. 3, No. 6, pp. 39-44, Nov-Dec 2012
- F.S. Gharehchopogh, I. Maleki, M. Farahmandian, "NEW APPROACH FOR SOLVING DYNAMIC TRAVELING SALESMAN PROBLEM WITH HYBRID GENETIC ALGORITHMS AND ANT COLONY OPTIMIZATION", International Journal of Computer Applications (IJCA), Vol .53, No.1, pp. 39-44, September 2012.
- Harun Rasit Er and Prof. Dr. Nadia Erdogan, ”PARALLEL GENETIC ALGORITHM TO SOLVE TRAVELLING SALESMAN PROBLEM ON MAPREDUCE FRAMEWORK USING HADOOP CLUSTER”, The International Journal of Soft Computing and Software Engineering [JSCSE], Vol. 3, No. 3, March 2013.
- Hashim Ali, Muhammad Haris, Fazl Hadi, Ahmadullah, Salman, Yasir Shah, “SOLVING TRAVELING SALESMAN PROBLEM THROUGH OPTIMIZATION TECHNIQUES USING GENETIC ALGORITHM AND ANT COLONY OPTIMIZATION” Journal of Applied Environmental and Biological Sciences, 2016.
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