Browsing by Author "Kunal, M."

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    Academic Curriculum Load Balancing using GA
    (2019) Chakradhar, M.; Charan, M.S.; Sai, R.U.; Kunal, M.; Murthy, Y.V.S.; Koolagudi, S.G.
    In the paper, we propose an algorithm using genetic alogithm to find out the optimal solution for the academic load balancing problem. The load balancing problem is to optimize the load of credits per semester in an academic curriculum. In the proposed method, we try to distribute the course load as evenly as possible so that the deviation from the mean credit load per each semester is as minimal as possible. The objective function is to distribute the credit load among all the semesters evenly such that the deviation from the mean credits per semester is minimal. The proposed approach explores the solution space using only mutation operators and does not operate using crossover as the solutions obtained using cross over does not create any newer and better solutions in the solution space.The algorithm is applied on three data sets and the results are compared with the solutions obtained using the existing approaches. The results obtained using the state of the art solution are either better than approaches or on par with the state of art optimal solutions. The solution set obtained using the proposed approach is well spread out through out all the periods and all the periods contain almost mean number of credits. � 2019 IEEE.
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    Academic Curriculum Load Balancing using GA
    (Institute of Electrical and Electronics Engineers Inc., 2019) Chakradhar, M.; Charan, M.S.; Sai, R.U.; Kunal, M.; Vishnu Srinivasa Murthy, Y.V.S.; Koolagudi, G.K.
    In the paper, we propose an algorithm using genetic alogithm to find out the optimal solution for the academic load balancing problem. The load balancing problem is to optimize the load of credits per semester in an academic curriculum. In the proposed method, we try to distribute the course load as evenly as possible so that the deviation from the mean credit load per each semester is as minimal as possible. The objective function is to distribute the credit load among all the semesters evenly such that the deviation from the mean credits per semester is minimal. The proposed approach explores the solution space using only mutation operators and does not operate using crossover as the solutions obtained using cross over does not create any newer and better solutions in the solution space.The algorithm is applied on three data sets and the results are compared with the solutions obtained using the existing approaches. The results obtained using the state of the art solution are either better than approaches or on par with the state of art optimal solutions. The solution set obtained using the proposed approach is well spread out through out all the periods and all the periods contain almost mean number of credits. © 2019 IEEE.
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    Application of Laubscher MRMR classification system in the design of open-pit chromite mines – A case study
    (World Researchers Associations, 2025) Dinesh, K.; Akhil, A.; Kunal, M.; Kumar, K.A.
    The study work was conducted at the Boula Chromite Mine site, focusing on geotechnical field observations in and around the area. The investigation aimed to comprehensively analyze surface and underground conditions, structural features, rock mass conditions and slope stability. The stereo net plot method was employed for slope stability analysis. Slope failures in rock masses were observed at the mine site at few locations, prompting us to delve into understanding the events and proposing precise recommendations for safe and efficient mining practices. The analysis of results formed the core objective of this study. To achieve the stated goal, a rational and systematic study in the field was conducted. This encompassed examining the geological and structural setup of rock formations, conducting field investigations to asses various geotechnical parameters, identifying the most influential factors affecting rock mass behavior, categorizing rock masses into groups based on similar behavior (rock mass classes), gathering structural data on slopes, classifying rock mass conditions using Laubscher’s rock mass classification and determining failure modes (planar, wedge, toppling and circular) in rock slopes through graphical analysis. The comprehensive rock mass classification and failure analysis were compiled in this work. The findings are crucial for identifying and thoroughly analyzing potential risks. This knowledge can play a pivotal role in ensuring the safety and efficiency of mining operations in and around the Boula Chromite Mine site. Moreover, the knowledge acquired from the study can be instrumental in planning and opening pit projects with similar geotechnical and mining conditions. The study thus provides valuable information for the broader field and contributes to the overall advancement of safe and effective mining practices. © 2025, World Researchers Associations. All rights reserved.