Forming competitively balanced teams

Abstract

This article examines the problem of assigning individuals to teams to make the teams as similar as possible to each other across multiple attributes. This may be complicated by a variety of constraints, including restrictions on whether specific individuals can or should be assigned to the same team. The problem arises in multiple contexts, including youth recreation leagues and academic programs or courses with mandated project groups. A model for the problem is proposed and various solution approaches are investigated, including mixed-integer programming and several heuristics. Supplementary materials are available for this article. Go to the publisher’s online edition of IIE Transactions for datasets, additional tables, detailed proofs, etc.

Keywords:

• Genetic algorithms
• heuristics
• personnel
• integer programming

Additional information

Notes on contributors

Paul A. Rubin

Paul A. Rubin is Professor Emeritus of Management Science in the Eli Broad College of Business at Michigan State University. He holds degrees in mathematics (A.B., Princeton University; Ph.D., Michigan State University) and statistics (M.S., Michigan State University). His primary research interest is in the application of integer programming models and algorithms. His previous publications have appeared in Operations Research, Decision Sciences, European Journal of Operational Research, and other journals perspicacious enough to accept them.

Lihui Bai

Lihui Bai is an Assistant Professor of Industrial Engineering Department at the University of Louisville. She received her Ph.D. in Industrial Engineering from the University of Florida. Her research interests are in the field of modeling and computation in operations research, with a recent focus on applications to energy systems. Her research has been published in Operations Research, Networks, and the Journal of Global Optimization, among others. She is a member of INFORMS, IIE, Alpha Pi Mu, and Alpha Iota Delta.