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This paper presents a multi-objective decision support model strategically integrating sustainability in decision making for student internship in higher education. Practical objective for fair and balanced planning is also incorporated. The model is automated in two stages – stage 1 involves data scraping from website using robot process automation while stage 2 applies multi-objective evolutionary algorithm (MOEA) to find best possible trade-offs between competing objectives. Novel sharing method is introduced and shown to work better with tournament selection in avoiding over degradation of individuals close to each other. Experimental results show that the proposed model is effective to automatically and objectively provide non-dominated choices for user to evaluate the trade-offs and make informed decision to trade-off between the competing objectives. While selecting a complete solution from the choices guarantee to be among the Pareto-frontiers, user can easily refine the solution to better suite and accommodate other requirements if any.
"Sustainable and Balanced Decision Support for Student Internship Planning", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2455-2631, Vol.9, Issue 4, page no.1120 - 1128, April-2024, Available :http://www.ijrti.org/papers/IJRTI2404150.pdf
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ISSN:
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator