research-article

The Effectiveness of Reference Point Selection Methods for Compromise Programming in Multi-Criteria Learning Path Search Algorithm

Authors:

Jafreezal Jaafar,

Thang Van Doan,

Duong Phan Lac,

Anh Ngoc BuiAuthors Info & Claims

IMMS '21: Proceedings of the 4th International Conference on Information Management and Management Science

Pages 296 - 302

https://doi.org/10.1145/3485190.3485236

Published: 02 December 2021 Publication History

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References

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Ngo Tung Son, Bui Ngoc Anh, Kieu Quoc Tuan, Nguyen Ba Son, Nguyen Hoang Son, and Jafreezal Jaafar. 2020. An Analysis of the Effectiveness of Emergency Distance Learning under COVID-19. In 2020 International Conference on Control, Robotics and Intelligent System (CCRIS 2020). Association for Computing Machinery, New York, NY, USA, 136–143.

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Wahid, Ratnaria; Ahmi, Aidi; Alam, A.S.A Ferdous (2020). Growth and Collaboration in Massive Open Online Courses: A Bibliometric Analysis. The International Review of Research in Open and Distributed Learning, 21(4), 292–322.

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N. T. Son, J. Jaafar, I. A. Aziz and B. N. Anh, "Meta-Heuristic Algorithms for Learning Path Recommender at MOOC," in IEEE Access, vol. 9, pp. 59093-59107, 2021.

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Ngo Tung Son, Dao Huy Dat, Nguyen Quang Trung, and Bui Ngoc Anh. 2017. Combination of Dimensionality Reduction and User Clustering for Collaborative-Filtering. In Proceedings of the 2017 International Conference on Computer Science and Artificial Intelligence (CSAI 2017). ACM, New York, NY, USA, 125-130.

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Tam, V., Lam, E.Y. & Fung, S.T. A new framework of concept clustering and learning path optimization to develop the next-generation e-learning systems. J. Comput. Educ. 1, 335–352 (2014). https://doi.org/10.1007/s40692-014-0016-8.

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Tang, T., & McCalla, G. (2010). Data Mining for Contextual Educational Recommendation and Evaluation Strategies. Chapman & Hall/CRC Data Mining and Knowledge Discovery Series, 257–272.

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Zhu, H., Tian, F., Wu, K., Shah, N., Chen, Y., Ni, Y., … Zheng, Q. (2018). A multi-constraint learning path recommendation algorithm based on knowledge map. Knowledge-Based Systems, 143, 102–114.

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Shi, D., Wang, T., Xing, H., & Xu, H. (2020). A learning path recommendation model based on a multidimensional knowledge graph framework for e-learning. Knowledge-Based Systems, 105618.

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Veldhuizen, D. A. Van, & Lamont, G. B. (2000). Multiobjective Evolutionary Algorithms: Analyzing the State-of-the-Art. Evolutionary Computation, 8(2). https://doi.org/10.1162/106365600568158.

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Gunantara, N. (2018). A review of multi-objective optimization: Methods and its applications. Cogent Engineering, 5(1). https://doi.org/10.1080/23311916.2018.1502242.

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Anagnostopoulos, G. G., Deriaz, M., & Konstantas, D. (2017). A multiobjective optimization methodology of tuning indoor positioning systems. 2017 International Conference on Indoor Positioning and Indoor Navigation (IPIN), 1–8. https://doi.org/10.1109/IPIN.2017.8115908.

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Miettinen, K. (1998). Nonlinear Multiobjective Optimization (Vol. 12). Springer US. https://doi.org/10.1007/978-1-4615-5563-6.

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Ojstersek, R., Brezocnik, M., & Buchmeister, B. (2020). Multi-objective optimization of production scheduling with evolutionary computation: A review. International Journal of Industrial Engineering Computations, 359–376. https://doi.org/10.5267/j.ijiec.2020.1.003.

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Sloss, A. N., & Gustafson, S. (2020). 2019 Evolutionary Algorithms Review. https://doi.org/10.1007/978-3-030-39958-0_16.

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Ma, H., Shen, S., Yu, M., Yang, Z., Fei, M., & Zhou, H. (2019). Multi-population techniques in nature inspired optimization algorithms: A comprehensive survey. Swarm and Evolutionary Computation, 44, 365–387. https://doi.org/10.1016/j.swevo.2018.04.011.

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Ringuest, J. L. (1992). Compromise Programming. In Multiobjective Optimization: Behavioral and Computational Considerations. Springer US. https://doi.org/10.1007/978-1-4615-3612-3_4.

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Ngo, S., Jaafar, J., Aziz, I., Nguyen, G., & Bui, A. (2021). Genetic Algorithm for Solving Multi-Objective Optimization in Examination Timetabling Problem. International Journal Of Emerging Technologies In Learning (IJET), 16(11), pp. 4-24.

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Son, Ngo T.; Jaafar, Jafreezal; Aziz, Izzatdin A.; Anh, Bui N. 2021. "A Compromise Programming for Multi-Objective Task Assignment Problem" Computers 10, no. 2: 15. https://doi.org/10.3390/computers10020015.

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Ngo, T.S.; Bui, N.A.; Tran, T.T.; Le, P.C.; Bui, D.C.; Nguyen, T.D.; Phan, L.D.; Kieu, Q.T.; Nguyen, B.S.; Tran, S.N. Some Algorithms to Solve a Bi-Objectives Problem for Team Selection. Appl. Sci. 2020, 10, 2700.

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Ngo Tung Son, Le Van Thanh, Tran Binh Duong, and Bui Ngoc Anh. 2018. A decision support tool for cross-functional team selection: case study in ACM-ICPC team selection. In Proceedings of the 2018 International Conference on Information Management & Management Science (IMMS '18). ACM, New York, NY, USA, 133-138.

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Ngo Tung Son*, Jafreezal B Jaafar, Nguyen Hoang Giang and Bui Ngoc Anh. 2021. A Genetic Algorithm for Multi-Objective Optimization in Complex Course Timetabling. In 2021 10th International Conference on Software and Computer Applications (ICSCA 2021), February 23-26, 2021, Kuala Lumpur, Malaysia. ACM, New York, NY, USA, 19 Pages. https://doi.org/10.1145/3457784.3457821.

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Son, N. T., Jaafar, J., Aziz, I. A., Anh, B. N., Binh, H. D. (2021). A Compromise Programming to Task Assignment Problem in Software Development Project. CMC-Computers, Materials & Continua, 69(3), 3429–3444.

Cited By

Son NNguyet Ha TJAAFAR JAnh BGiang T(2023)Some Metaheuristics for Tourist Trip Design Problem2023 IEEE Symposium on Industrial Electronics & Applications (ISIEA)10.1109/ISIEA58478.2023.10212154(1-10)Online publication date: 15-Jul-2023
https://doi.org/10.1109/ISIEA58478.2023.10212154
Ngo SJaafar JIzzatdin ATong GBui A(2022)Some metaheuristic algorithms for solving multiple cross-functional team selection problemsPeerJ Computer Science10.7717/peerj-cs.10638(e1063)Online publication date: 9-Aug-2022
https://doi.org/10.7717/peerj-cs.1063
Ngo TJaafar JAziz IAftab MNguyen HBui N(2022)Metaheuristic Algorithms Based on Compromise Programming for the Multi-Objective Urban Shipment ProblemEntropy10.3390/e2403038824:3(388)Online publication date: 9-Mar-2022
https://doi.org/10.3390/e24030388

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IMMS '21: Proceedings of the 4th International Conference on Information Management and Management Science

August 2021

332 pages

ISBN:9781450384278

DOI:10.1145/3485190

Copyright © 2021 ACM.

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Published: 02 December 2021

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IMMS 2021

IMMS 2021: 2021 4th International Conference on Information Management and Management Science

August 27 - 29, 2021

Chengdu, China

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Cited By

Son NNguyet Ha TJAAFAR JAnh BGiang T(2023)Some Metaheuristics for Tourist Trip Design Problem2023 IEEE Symposium on Industrial Electronics & Applications (ISIEA)10.1109/ISIEA58478.2023.10212154(1-10)Online publication date: 15-Jul-2023
https://doi.org/10.1109/ISIEA58478.2023.10212154
Ngo SJaafar JIzzatdin ATong GBui A(2022)Some metaheuristic algorithms for solving multiple cross-functional team selection problemsPeerJ Computer Science10.7717/peerj-cs.10638(e1063)Online publication date: 9-Aug-2022
https://doi.org/10.7717/peerj-cs.1063
Ngo TJaafar JAziz IAftab MNguyen HBui N(2022)Metaheuristic Algorithms Based on Compromise Programming for the Multi-Objective Urban Shipment ProblemEntropy10.3390/e2403038824:3(388)Online publication date: 9-Mar-2022
https://doi.org/10.3390/e24030388

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