A New Version of the Golden Eagle Optimizer Algorithm And Its Application For Solving A Trio-Objective Skillful Team Formation Problem In A Social Network

[1] Zitong Wang, Yan Pei, and Jianqiang Li. A survey on search strategy of evolutionary multi-objective optimization algorithms. Applied Sciences, 13(7), 2023. Search in Google Scholar

[2] Ahmed M. Nassef, Mohammad Ali Abdelkareem, Hussein M. Maghrabie, and Ahmad Baroutaji. Review of metaheuristic optimization algorithms for power systems problems. Sustainability, 15(12), 2023. Search in Google Scholar

[3] Mohammed A. Khasawneh and Anjali Awasthi. Intelligent meta-heuristic-based optimization of traffic light timing using artificial intelligence techniques. Electronics, 12(24), 2023. Search in Google Scholar

[4] Sachin Desale, Akhtar Rasool, Sushil Andhale, and Priti Rane. Heuristic and meta-heuristic algorithms and their relevance to the real world: A survey. International Journal of Computer Engineering in research treands, 351:2349–7084, 01 2015. Search in Google Scholar

[5] J. Kennedy and R. Eberhart. Particle swarm optimization. In Proceedings of ICNN’95 - International Conference on Neural Networks, volume 4, pages 1942–1948, Perth, WA, Australia, 1995. IEEE. Search in Google Scholar

[6] Alireza Askarzadeh. A novel metaheuristic method for solving constrained engineering optimization problems: Crow search algorithm. Computers & Structures, 169:1–12, June 2016. Search in Google Scholar

[7] Julius Odili. African Buffalo Optimization. International Journal of Software Engineering & Computer Systems, 2:28–50, February 2016. Search in Google Scholar

[8] Mohit Jain, Vijander Singh, and Asha Rani. A novel nature-inspired algorithm for optimization: Squirrel search algorithm. Swarm and Evolutionary Computation, 44:148–175, February 2019. Search in Google Scholar

[9] Sankalap Arora and Satvir Singh. Butterfly optimization algorithm: a novel approach for global optimization. Soft Computing, 23(3):715–734, February 2019. Search in Google Scholar

[10] R. Venkata Rao. Jaya: A simple and new optimization algorithm for solving constrained and unconstrained optimization problems. International Journal of Industrial Engineering Computations, pages 19–34, 2016. Search in Google Scholar

[11] Abdolkarim Mohammadi-Balani, Mahmoud Dehghan Nayeri, Adel Azar, and Mohammadreza Taghizadeh-Yazdi. Golden eagle optimizer: A nature-inspired metaheuristic algorithm. Computers & Industrial Engineering, 152:107050, February 2021. Search in Google Scholar

[12] Zubayer Alam Khan, Shoayeb Fahim Akhter, Sakib Islam, and Fahim Abid. A Golden Eagle Optimization Based MPPT Control For Partial Shading Conditions. In 2022 IEEE International Conference on Power Electronics, Smart Grid, and Renewable Energy (PESGRE), pages 1–6, Trivan-drum, India, January 2022. IEEE. Search in Google Scholar

[13] Ji-Xiang Lv, Li-Jun Yan, Shu-Chuan Chu, Zhi-Ming Cai, Jeng-Shyang Pan, Xian-Kang He, and Jian-Kai Xue. A new hybrid algorithm based on golden eagle optimizer and grey wolf optimizer for 3D path planning of multiple UAVs in power inspection. Neural Computing and Applications, 34(14):11911–11936, July 2022. Search in Google Scholar

[14] Xiangjie Kong, Yajie Shi, Shuo Yu, Jiaying Liu, and Feng Xia. Academic social networks: Modeling, analysis, mining and applications. Journal of Network and Computer Applications, 132:86–103, April 2019. Search in Google Scholar

[15] Nasreen S Jessani, Carly Babcock, Sameer Siddiqi, Melissa Davey-Rothwel, Shirley Ho, and David R Holtgrave. Relationships between public health faculty and decision makers at four governmental levels: a social network analysis. Evidence & Policy, 14(03):499–522, August 2018. Search in Google Scholar

[16] Chuqing Dong and Hyejoon Rim. Exploring nonprofit-business partnerships on Twitter from a network perspective. Public Relations Review, 45(1):104–118, March 2019. Search in Google Scholar

[17] Senjuti Basu Roy, Laks V.S. Lakshmanan, and Rui Liu. From Group Recommendations to Group Formation. In Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pages 1603–1616, Melbourne Victoria Australia, May 2015. ACM. Search in Google Scholar

[18] Xinyu Wang, Zhou Zhao, and Wilfred Ng. A Comparative Study of Team Formation in Social Networks. In Matthias Renz, Cyrus Shahabi, Xiao-fang Zhou, and Muhammad Aamir Cheema, editors, Database Systems for Advanced Applications, volume 9049, pages 389–404. Springer International Publishing, Cham, 2015. Series Title: Lecture Notes in Computer Science. Search in Google Scholar

[19] Xinyu Wang, Zhou Zhao, and Wilfred Ng. USTF: A Unified System of Team Formation. IEEE Transactions on Big Data, 2(1):70–84, March 2016. Search in Google Scholar

[20] Wynand Jc Van Staden and Etienne Van Der Poel. Team formation in digital forensics. In 2016 Information Security for South Africa (ISSA), pages 91–97, Johannesburg, South Africa, August 2016. IEEE. Search in Google Scholar

[21] Mohammed Alqahtani, Susan Gauch, Omar Salman, Mohammed Ibrahim, and Reem Al-Saffar. Diverse Group Formation based on Multiple Demographic Features. In Proceedings of the 12th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management, pages 169–178, Budapest, Hungary, 2020. SCITEPRESS - Science and Technology Publications. Search in Google Scholar

[22] Yashar Najaflou and Kris Bubendorfer. In Pursuit of the Wisest: Building Cost-Effective Teams of Experts. In 2017 IEEE 13th International Conference on e-Science (e-Science), pages 158–167, Auckland, October 2017. IEEE. Search in Google Scholar

[23] Mehdi Kargar and Aijun An. TeamExp: Topk Team Formation in Social Networks. In 2011 IEEE 11th International Conference on Data Mining Workshops, pages 1231–1234, Vancouver, BC, Canada, December 2011. IEEE. Search in Google Scholar

[24] Theodoros Lappas, Kun Liu, and Evimaria Terzi. Finding a team of experts in social networks. In Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining, pages 467–476, Paris France, June 2009. ACM. Search in Google Scholar

[25] Sagarika Khandelwal. Building a team of experts using integer linear programming (ilp). Master’s thesis, University of Windsor, Windsor, Ontario, Canada, 2019. Search in Google Scholar

[26] Arne Schulz. A new mixed-integer programming formulation for the maximally diverse grouping problem with attribute values. Annals of Operations Research, 318:501–530, 2022. Search in Google Scholar

[27] Che Zhamri, Zhamri Che Ani, Azman Yasin, Mohd Zabidin Husin, and Zauridah Hamid. A method for group formation using genetic algorithm. International Journal on Computer Science and Engineering, 02:3060–3064, 01 2010. Search in Google Scholar

[28] André Luiz Netto Casotti and Renato A. Krohling. A multi-objective formulation for the team formation problem using krippendorff’s disagreement and sociometric cohesion with pareto-solutions obtained via evolutionary algorithms. Computers & Operations Research, 161:106444, 2024. Search in Google Scholar

[29] Jose G. M. Esgario, Iago E. da Silva, and Renato A. Krohling. Application of genetic algorithms to the multiple team formation problem, 2019. Search in Google Scholar

[30] Gaganmeet Kaur Awal and K. K. Bharadwaj. Team formation in social networks based on collective intelligence – an evolutionary approach. Applied Intelligence, 41(2):627–648, September 2014. Search in Google Scholar

[31] M. Niveditha, G. Swetha, U. Poornima, and Radha Senthilkumar. A genetic approach for tri-objective optimization in team formation. In 2016 Eighth International Conference on Advanced Computing (ICoAC), pages 123–130, Chennai, India, January 2017. IEEE. Search in Google Scholar

[32] Javad Basiri, Fattaneh Taghiyareh, and Amineh Ghorbani. Collaborative team formation using brain drain optimization: a practical and effective solution. World Wide Web, 20(6):1385–1407, November 2017. Search in Google Scholar

[33] Ali Bagherinia and Elham Amini. An optimization approach for forming a team of experts in social networks. International Journal of Advance Robotics & Expert Systems (JARES), 1(2):6, 2018. Search in Google Scholar

[34] Md. Abdul Kader and Kamal Z. Zamli. Comparative study of five metaheuristic algorithms for team formation problem. In Human-Centered Technology for a Better Tomorrow, Lecture Notes in Mechanical Engineering, pages 133–143. Springer, October 2021. First Online: 02 October 2021. Search in Google Scholar

[35] Nihal Berktas¸ and Hande Yaman. A Branch-and-Bound Algorithm for Team Formation on Social Networks. INFORMS Journal on Computing, 33(3):1162–1176, July 2021. Search in Google Scholar

[36] Mehdi Kargar and Aijun An. Discovering top-k teams of experts with/without a leader in social networks. In Proceedings of the 20th ACM international conference on Information and knowledge management, pages 985–994, Glasgow Scotland, UK, October 2011. ACM. Search in Google Scholar

[37] Mehdi Kargar, Aijun An, and Morteza Zihayat. Efficient Bi-objective Team Formation in Social Networks. In David Hutchison, Takeo Kanade, Josef Kittler, Jon M. Kleinberg, Friedemann Mattern, John C. Mitchell, Moni Naor, Oscar Nierstrasz, C. Pandu Rangan, Bernhard Steffen, Madhu Sudan, Demetri Terzopoulos, Doug Tygar, Moshe Y. Vardi, Gerhard Weikum, Peter A. Flach, Tijl De Bie, and Nello Cristianini, editors, Machine Learning and Knowledge Discovery in Databases, volume 7524, pages 483–498. Springer Berlin Heidelberg, Berlin, Heidelberg, 2012. Series Title: Lecture Notes in Computer Science. Search in Google Scholar

[38] Ioannis Kouvatis, Konstantinos Semertzidis, Maria Zerva, Evaggelia Pitoura, and Panayiotis Tsaparas. Forming Compatible Teams in Signed Networks, 2020. Search in Google Scholar

[39] Timo Wolf, Adrian Schröter, Daniela Damian, Lucas D. Panjer, and Thanh H.D. Nguyen. Mining Task-Based Social Networks to Explore Collaboration in Software Teams. IEEE Software, 26(1):58–66, January 2009. Search in Google Scholar

[40] N. V. Chawla, K. W. Bowyer, L. O. Hall, and W. P. Kegelmeyer. SMOTE: Synthetic Minority Over-sampling Technique. Journal of Artificial Intelligence Research, 16:321–357, June 2002. Search in Google Scholar

[41] Paul F. Lazarsfeld and R. Merton. Friendship as Social process: a substantive and methodological analysis. 1964. Search in Google Scholar

[42] Miller McPherson, Lynn Smith-Lovin, and James M Cook. Birds of a Feather: Homophily in Social Networks. Annual Review of Sociology, 27(1):415–444, August 2001. Search in Google Scholar

[43] William G. Stillwell, David A. Seaver, and Ward Edwards. A comparison of weight approximation techniques in multiattribute utility decision making. Organizational Behavior and Human Performance, 28(1):62–77, August 1981. Search in Google Scholar

[44] Wikipedia contributors. Golden eagles in human culture, Accessed: 2024-03-27. Accessed from Wikipedia, the free encyclopedia. Search in Google Scholar

[45] Zhi-Kai Fan, Kuo-Lung Lian, and Jia-Fu Lin. A new golden eagle optimization with stooping behaviour for photovoltaic maximum power tracking under partial shading. Energies, 16(15), 2023. Search in Google Scholar

[46] Zamli KZ. UMP Dataset, April 2024. Search in Google Scholar

[47] Zamli KZ. IMDB Dataset, April 2024. Search in Google Scholar

[48] Zamli KZ. ACM Dataset, April 2024. Search in Google Scholar

[49] Zamli KZ. DBLP Dataset, April 2024. Search in Google Scholar

[50] Md. Abdul Kader and Kamal Z. Zamli. Adopting Jaya Algorithm for Team Formation Problem. In Proceedings of the 2020 9th International Conference on Software and Computer Applications, pages 62–66, Langkawi Malaysia, February 2020. ACM. Search in Google Scholar

[51] Aris Anagnostopoulos, Luca Becchetti, Carlos Castillo, Aristides Gionis, and Stefano Leonardi. Power in unity: forming teams in large-scale community systems. In Proceedings of the 19th ACM international conference on Information and knowledge management, pages 599–608, Toronto ON Canada, October 2010. ACM. Search in Google Scholar

[52] Alain Mille, Fabien Gandon, Jacques Misselis, Michael Rabinovich, and Steffen Staab. Online team formation in social networks. In Proceedings of the 21st international conference on World Wide Web, Lyon France, April 2012. ACM. Search in Google Scholar

[53] Computer Science Department, Faculty of Computers and Informatics, Suez Canal University, Ismailia, 41522, Egypt and Walaa H. El-Ashmawi. An Improved African Buffalo Optimization Algorithm for Collaborative Team Formation in Social Network. International Journal of Information Technology and Computer Science, 10(5):16–29, May 2018. Search in Google Scholar

[54] Ronald W. Morrison and Kenneth A. De Jong. Measurement of population diversity. In Pierre Collet, Cyril Fonlupt, Jin-Kao Hao, Evelyne Lutton, and Marc Schoenauer, editors, Artificial Evolution, pages 31–41, Berlin, Heidelberg, 2002. Springer Berlin Heidelberg. Search in Google Scholar