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Thus, this requirement leads to the problem of generating tests with equal difficulties, which is also known as the specific case of generating tests with a single objective. However, in practice, multiple requirements (objectives) are enforced while making tests. For example, teachers may require the generated tests to have the same difficulty and the same test duration. In this paper, we propose the use of Multiswarm Multiobjective Particle Swarm Optimization (MMPSO) for generating<jats:italic>k<\/jats:italic>tests with multiple objectives in a single run. Additionally, we also incorporate Simulated Annealing (SA) to improve the diversity of tests and the accuracy of solutions. The experimental results with various criteria show that our approaches are effective and efficient for the problem of generating multiple tests.<\/jats:p>","DOI":"10.1155\/2020\/7081653","type":"journal-article","created":{"date-parts":[[2020,8,1]],"date-time":"2020-08-01T23:34:59Z","timestamp":1596324899000},"page":"1-15","source":"Crossref","is-referenced-by-count":2,"title":["Multiswarm Multiobjective Particle Swarm Optimization with Simulated Annealing for Extracting Multiple Tests"],"prefix":"10.1155","volume":"2020","author":[{"given":"Toan","family":"Bui","sequence":"first","affiliation":[{"name":"Faculty of Information Technology, Ho Chi Minh City University of Technology (HUTECH), Ho Chi Minh, Vietnam"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tram","family":"Nguyen","sequence":"additional","affiliation":[{"name":"Faculty of Information Technology, Nong Lam University, Ho Chi Minh, Vietnam"},{"name":"Department of Computer Science, Faculty of Electrical 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