A Comparative Evaluation of GA and SA TSP in a Supply Chain Network

Author:

Rao T Srinivas

Publisher

Elsevier BV

Subject

General Medicine

Reference5 articles.

1. Tatavarthy Srinivas Rao Balkrishna Rao, Naidu and Mallikharjuna Babu,“A Novel and Efficient Approach for Materials Demand Aggregation using Genetic Algorithm”, International Journal of Computer Science and Network Security, Vol. 9, No. 4, pp. 203–212, April 2009J. Clerk Maxwell, A Treatise on Electricity and Magnetism, 3rd ed., vol. 2. Oxford: Clarendon, 1892, pp. 68–73.

2. Black, Paul E. (2 February 2005). “greedy algorithm”. Dictionary of Algorithms and Data Structures. U.S. National Institute of Standards and Technology (NIST). Retrieved 17 August 2012.

3. Applegate, D. L.; Bixby, R. M.; Chvátal, V.; Cook, W. J. (2006), The Traveling Salesman Problem, ISBN 0-691-12993-2.Y.

4. Shyi-Ming Chen, Chih-Yao Chen”, Parallelized genetic Ant Colony System for solving the travelling salesman problem”Expert systems with Applications 38(2011) 3873–3883 Elsevier Journal.

5. Shalini singh, Ejaj Aslam Lodhi”, Study of variation in tsp using genetic algorithm and its operator comparison” International Journal of Soft Computing and Engineering(IJSCE)ISSN:2231–2307 volume 3, Issue 2 May 2013.

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