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Comparison of Metaheuristics for the Allocation of Resources for an After-School Program in Remote Areas of India

Publication Type : Book Chapter

Thematic Areas : Technologies & Education (AmritaCREATE)

Publisher : Machine Learning and Metaheuristics Algorithms, and Applications.

Source : Machine Learning and Metaheuristics Algorithms, and Applications, p.225-233 (2020)

Url : https://www.scopus.com/inward/record.uri?eid=2-s2.0-85085726681&doi=10.1007%2f978-981-15-4301-2_20&partnerID=40&md5=b73ae8c509c178491a2dfc278226da06

ISBN : 9789811543005

Campus : Amritapuri

School : Department of Computer Science and Engineering, School of Engineering

Center : Amrita Center For Research in Analytics, AmritaCREATE

Department : Computer Science

Year : 2020

Abstract : This paper describes an after-school education program in rural India. The program maintains 53 education centers in remote villages in 21 states of India. For the allocation of resources, we first describe the results of an multi-attribute utility assessment, where 130 teachers, coordinators, and people associated with the program specified their opinion on factors that are most important on running a successful after-school education center. We then formulate the problem of optimal resource allocating as a generalized assignment problem. To solve this problem, three different metaheuristics are compared: iterated hill climbing, tabu search, and simulated annealing. It is found that tabu search is giving the best performance.

Cite this Research Publication : G. Gutjahr, Menon, R., and Prof. Prema Nedungadi, “Comparison of Metaheuristics for the Allocation of Resources for an After-School Program in Remote Areas of India”, in Machine Learning and Metaheuristics Algorithms, and Applications, 2020, pp. 225-233.

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