Organizational research has shown that effectively structuring the
resources (human, informational, computational) available to an
organization can significantly improve its collective computational
capacity. Central to this improved capacity is the manner in which the
organization's member agents are related. This study is an initial
investigation into the role and potential of interagent ties in
computational teaming. A computational team-based model, designed to more
fully integrate agent ties, is created and presented. It is applied to a
bulk manufacturing process-planning problem and its performance compared
against a previously tested agent-based algorithm without these agent
relationships. The performance of the new agent method showed significant
improvement over the previous method: improving solution quality 280% and
increasing solution identification per unit time an entire order of
magnitude. A statistical examination of the new algorithm confirms that
agent interdependencies are the strongest and most consistent performance
effects leading to the observed improvements. This study illustrates that
the interagent ties associated with team collaboration can be a highly
effective method of improving computational design performance, and the
results are promising indications that the application of organization
constructs within a computational context may significantly improve
computational problem solving.