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Experiments were conducted comparing the static, dynamic and adaptive penalty functions on varying the space constraint. The adaptive penalty function method yields the best results in terms of minimum query processing cost and achieves the optimality, scalability and feasibility of the problem on varying the lattice dimensions and on increasing the number of user queries. The authors proposed work has been compared with other evolutionary algorithms i.e. PSO and genetic algorithm and yields better results in terms of minimum total query processing cost of the materialized views.<\/jats:p>","DOI":"10.4018\/ijncr.2019040101","type":"journal-article","created":{"date-parts":[[2019,3,21]],"date-time":"2019-03-21T13:18:30Z","timestamp":1553174310000},"page":"1-17","source":"Crossref","is-referenced-by-count":4,"title":["Handling Constraints Using Penalty Functions in Materialized View Selection"],"prefix":"10.4018","volume":"8","author":[{"given":"Anjana","family":"Gosain","sequence":"first","affiliation":[{"name":"USICT, GGSIPU, New Delhi, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kavita","family":"Sachdeva","sequence":"additional","affiliation":[{"name":"SGT University, Gurugram, India"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"2432","reference":[{"key":"IJNCR.2019040101-0","doi-asserted-by":"publisher","DOI":"10.1016\/j.amc.2013.02.017"},{"key":"IJNCR.2019040101-1","doi-asserted-by":"publisher","DOI":"10.1016\/S0045-7825(01)00323-1"},{"key":"IJNCR.2019040101-2","doi-asserted-by":"crossref","unstructured":"Coello Carlos, A. 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