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Journal of the Operational Research Society Volume 62, 2011 - Issue 1
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Theoretical Paper

A hybrid genetic algorithmic approach to the maximally diverse grouping problem

Z P FanNortheastern UniversityShenyangChina
,
Y ChenShanghai University of Finance & EconomicsShanghaiChina
,
J MaCity University of Hong KongKowloonHong Kong
&
S ZengUniversity of ArizonaUSA
Pages 92-99 | Received 01 Aug 2007, Accepted 01 Aug 2009, Published online: 21 Dec 2017

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Teresa Galvão Dias & José Borges. (2017) A new algorithm to create balanced teams promoting more diversity. European Journal of Engineering Education 42:6, pages 1365-1377.
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M Gallego, M Laguna, R Martí & A Duarte. (2013) Tabu search with strategic oscillation for the maximally diverse grouping problem. Journal of the Operational Research Society 64:5, pages 724-734.
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Kavita Singh & Shyam Sundar. (2019) A new hybrid genetic algorithm for the maximally diverse grouping problem. International Journal of Machine Learning and Cybernetics 10:10, pages 2921-2940.
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Jack Brimberg, Nenad Mladenović, Raca Todosijević & Dragan Urošević. (2017) Solving the capacitated clustering problem with variable neighborhood search. Annals of Operations Research 272:1-2, pages 289-321.
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Xiangjing Lai & Jin-Kao Hao. (2016) Iterated variable neighborhood search for the capacitated clustering problem. Engineering Applications of Artificial Intelligence 56, pages 102-120.
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Xiangjing Lai & Jin-Kao Hao. (2016) Iterated maxima search for the maximally diverse grouping problem. European Journal of Operational Research 254:3, pages 780-800.
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Putu Indah Ciptayani, Kadek Cahya Dewi & I Wayan Budi Sentana. (2016) Student grouping using adaptive genetic algorithm. Student grouping using adaptive genetic algorithm.
Chun-Hao Chen, Cheng-Yu Lu, Tzung-Pei Hong & Ja-Hwung Su. (2016) Using grouping genetic algorithm to mine diverse group stock portfolio. Using grouping genetic algorithm to mine diverse group stock portfolio.
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Anna Martínez-Gavara, Vicente Campos, Micael Gallego, Manuel Laguna & Rafael Martí. (2015) Tabu search and GRASP for the capacitated clustering problem. Computational Optimization and Applications 62:2, pages 589-607.
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Kayse Lee Maass, Vera Mann Hey Lo, Anna Weiss & Mark S. Daskin. (2015) Maximizing Diversity in the Engineering Global Leadership Cultural Families. Interfaces 45:4, pages 293-304.
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Yulei Pang, Raymond Mugno, Xiaozhen Xue & Huaying Wang. (2015) Constructing Collaborative Learning Groups with Maximum Diversity Requirements. Constructing Collaborative Learning Groups with Maximum Diversity Requirements.
Jill Johnes. (2015) Operational Research in education. European Journal of Operational Research 243:3, pages 683-696.
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Jack Brimberg, Nenad Mladenović & Dragan Urošević. (2015) Solving the maximally diverse grouping problem by skewed general variable neighborhood search. Information Sciences 295, pages 650-675.
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Elena Fernández, Jörg Kalcsics & Stefan Nickel. (2013) The maximum dispersion problem. Omega 41:4, pages 721-730.
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Francisco J. Rodriguez, M. Lozano, C. García-Martínez & Jonathan D. González-Barrera. (2013) An artificial bee colony algorithm for the maximally diverse grouping problem. Information Sciences 230, pages 183-196.
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Zhenliang Liao, Phillip M. Hannam, Xiaowei Xia & Tingting Zhao. (2012) Integration of multi-technology on oil spill emergency preparedness. Marine Pollution Bulletin 64:10, pages 2117-2128.
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Zhenliang Liao, Xuewei Mao, Phillip M. Hannam & Tingting Zhao. (2012) Adaptation methodology of CBR for environmental emergency preparedness system based on an Improved Genetic Algorithm. Expert Systems with Applications 39:8, pages 7029-7040.
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