Constrained group balancing: Why does it work

Dmitry Krass

doi:10.1016/j.ejor.2010.02.011

Constrained group balancing: Why does it work

2010-10-01

15

PRE

AI

DOI：10.1016/j.ejor.2010.02.011

原文链接

原文求助

摘要

En 中文

We consider a problem where a set of objects possessing multiple attributes must be partitioned into a certain number of groups so that the groups are as balanced as possible with respect to the number of objects possessing each attribute. This multi-criteria decision problem arises in a variety of practical applications, ranging from assigning students to study groups to designing level schedules for JIT assembly lines. A direct approach, enforcing balance through hard constraints, may lead to infeasibility, but works well in practice. We analyze this phenomenon from the worst-case and empirical perspectives, as well as through an in-depth analysis of one representative practical application - the design of student groups at the Rotman School of Management, University of Toronto. The goals of the analysis are to understand what classes of balancing problems may contain infeasible instances and how prevalent such instances are within these classes, as well as to synthesize practical managerial insights that a decision maker could follow in order to increase the chances that balanced groups can be found. (C) 2010 Elsevier B.V. All rights reserved.

Keyword:

Decision support

Combinatorial optimization

OR applications - education

Group balancing

Constrained group balancing: Why does it work

摘要

期刊

机构