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Theoretical Paper

Design of balanced MBA student teams

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Pages 60-66 | Received 01 Oct 2002, Accepted 01 Apr 2004, Published online: 21 Dec 2017

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Read on this site (2)

Paul A. Rubin & Lihui Bai. (2015) Forming competitively balanced teams. IIE Transactions 47:6, pages 620-633.
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Richard Forrester, Kevin Hutson & Thanh To. (2013) Improving the quality of the assignment of students to first-year seminars. OR Insight 26:2, pages 120-139.
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Articles from other publishers (28)

Andrew BowersMelissa R. Bowers, Nana BryanPaolo Letizia & Spencer Murphy. (2023) Forming Student Teams to Incorporate Soft Skills and Commonality of Schedule. INFORMS Journal on Applied Analytics 53:2, pages 111-127.
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Marcos de S. Oliveira, Sergio R. de M. Queiroz & Francisco de A.T. de Carvalho. (2022) Unsupervised feature selection method based on iterative similarity graph factorization and clustering by modularity. Expert Systems with Applications 208, pages 118092.
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Xiao Yang, Zonghui Cai, Ting Jin, Zheng Tang & Shangce Gao. (2022) A three-phase search approach with dynamic population size for solving the maximally diverse grouping problem. European Journal of Operational Research 302:3, pages 925-953.
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Gábor Kondor. (2022) NP-hardness of m-dimensional weighted matching problems. Theoretical Computer Science 930, pages 33-36.
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R. Martín-Santamaría, J. Sánchez-Oro, S. Pérez-Peló & A. Duarte. (2022) Strategic oscillation for the balanced minimum sum-of-squares clustering problem. Information Sciences 585, pages 529-542.
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Eduardo Canale, Franco Robledo, Pablo Sartor & Luis Stábile. (2021) Solving the Max-Diversity Orthogonal Regrouping Problem by an Integer Linear Programming Model and a GRASP/VND with Path-Relinking Approach. Symmetry 14:1, pages 18.
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Qing Zhou, Jin-Kao Hao & Qinghua Wu. (2021) Responsive threshold search based memetic algorithm for balanced minimum sum-of-squares clustering. Information Sciences 569, pages 184-204.
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Matías Banchero, Franco Robledo, Pablo Romero, Pablo Sartor & Camilo Servetti. 2021. Variable Neighborhood Search. Variable Neighborhood Search 58 70 .
Qin Sun, Xiangjing Lai & Qiang Yao. (2020) An iterated variable neighborhood search algorithm for the balanced minimum sum-of-squares clustering problem. An iterated variable neighborhood search algorithm for the balanced minimum sum-of-squares clustering problem.
Mohammed Najib Haouas, Daniel Aloise & Gilles Pesant. 2020. Integration of Constraint Programming, Artificial Intelligence, and Operations Research. Integration of Constraint Programming, Artificial Intelligence, and Operations Research 256 272 .
Ewa Andrejczuk, Filippo Bistaffa, Christian Blum, Juan A. Rodríguez-Aguilar & Carles Sierra. (2019) Synergistic team composition: A computational approach to foster diversity in teams. Knowledge-Based Systems 182, pages 104799.
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Pierre Hansen, Nenad Mladenović, Jack Brimberg & José A. Moreno Pérez. 2019. Handbook of Metaheuristics. Handbook of Metaheuristics 57 97 .
Ewa Andrejczuk, Juan A. Rodriguez-Aguilar, Carles Sierra, Carme Roig & Yolanda Parejo-Romero. (2018) Don’t Leave Anyone Behind: Achieving Team Performance Through Diversity. Don’t Leave Anyone Behind: Achieving Team Performance Through Diversity.
A. W. El-Bouri & A. Al-Zaidi. (2017) Allocation of college students to business majors with the aid of a linear programming model. Allocation of college students to business majors with the aid of a linear programming model.
Leandro R. Costa, Daniel Aloise & Nenad Mladenović. (2017) Less is more: basic variable neighborhood search heuristic for balanced minimum sum-of-squares clustering. Information Sciences 415-416, pages 247-253.
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Artem Pyatkin, Daniel Aloise & Nenad Mladenović. (2017) NP-Hardness of balanced minimum sum-of-squares clustering. Pattern Recognition Letters 97, pages 44-45.
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Jack Brimberg, Stefana Janićijević, Nenad Mladenović & Dragan Urošević. (2015) Solving the clique partitioning problem as a maximally diverse grouping problem. Optimization Letters 11:6, pages 1123-1135.
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Jack Brimberg, Nenad Mladenović & Dragan Urošević. 2016. Models, Algorithms and Technologies for Network Analysis. Models, Algorithms and Technologies for Network Analysis 3 38 .
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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Sergio García, Valentina Cacchiani, Lieselot Vanhaverbeke & Martin Bischoff. (2012) The table placement problem: a research challenge at the EWI 2007. TOP 22:1, pages 208-226.
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Theresa M. Roeder & Robert M. Saltzman. (2014) Schedule-Based Group Assignment Using Constraint Programming. INFORMS Transactions on Education 14:2, pages 63-72.
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Marco Caserta & Stefan Voß. 2013. Hybrid Metaheuristics. Hybrid Metaheuristics 118 129 .
Dmitry Krass & Anton Ovchinnikov. (2010) Constrained group balancing: Why does it work. European Journal of Operational Research 206:1, pages 144-154.
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Pierre Hansen, Nenad Mladenović & José A. Moreno Pérez. (2009) Variable neighbourhood search: methods and applications. Annals of Operations Research 175:1, pages 367-407.
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Amy Cohn, Michael Magazine & George Polak. (2009) Rank‐Cluster‐and‐Prune: An algorithm for generating clusters in complex set partitioning problems. Naval Research Logistics (NRL) 56:3, pages 215-225.
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Pierre Hansen, Nenad Mladenović & José A. Moreno Pérez. (2008) Variable neighbourhood search: methods and applications. 4OR 6:4, pages 319-360.
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Pierre Hansen & Nenad Mladenović. 2009. Encyclopedia of Optimization. Encyclopedia of Optimization 3975 3989 .
Dmitry Krass & Anton Ovchinnikov. (2006) The University of Toronto’s Rotman School of Management Uses Management Science to Create MBA Study Groups. Interfaces 36:2, pages 126-137.
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