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Query Optimization using Modified Ant Colony Algorithm

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2017
Ajay Wagh, Varsha Nemade

Ajay Wagh and Varsha Nemade. Query Optimization using Modified Ant Colony Algorithm. International Journal of Computer Applications 167(2):29-33, June 2017. BibTeX

	author = {Ajay Wagh and Varsha Nemade},
	title = {Query Optimization using Modified Ant Colony Algorithm},
	journal = {International Journal of Computer Applications},
	issue_date = {June 2017},
	volume = {167},
	number = {2},
	month = {Jun},
	year = {2017},
	issn = {0975-8887},
	pages = {29-33},
	numpages = {5},
	url = {},
	doi = {10.5120/ijca2017914185},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}


Query optimization is challenging task in database. Many different types of techniques used to optimize query. Heuristic Greedy, Iterative Improvement and Ant Colony algorithms is being used to query optimization. Ant colony Algorithm used to find optimal solution for different type of problems. In this paper we modify Ant Colony Algorithm for query optimization and will show the comparison execution time between Heuristic based optimization, Ant Colony Optimization and Modified Ant Colony optimization algorithms. After implementation of said existing algorithms and modified Ant Colony optimization algorithms we found that modified Ant colony taking less computation time as compare to others algorithms.


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Query Optimization, Heuristic-based optimizers, Ant-Colony, Modified Ant Colony.