In the paper a genetic algorithm approach to form potential Collaborative Networked Organizations (CNOs) is presented. When analyzing a set of companies that are potential partners of a CNO, it is possible to collect specific data from each company through which evaluate, once aggregated, for which Strategic Objective (SO) the potential aggregation is most suited. At this purpose a metric, consisting in a set of performance parameters related to different SO types, has been created. Given a large number of companies, through a genetic algorithm approach is then possible to set a specific objective function related to a particular SO (eg. maximize potential creation of new Business Opportunities), and to find the cluster (or clusters) of companies that maximizes the objective function.
A Genetic algorithm approach for Collaborative Networked Organizations partners selection
TIACCI, Lorenzo
;CARDONI, ANDREA
2012
Abstract
In the paper a genetic algorithm approach to form potential Collaborative Networked Organizations (CNOs) is presented. When analyzing a set of companies that are potential partners of a CNO, it is possible to collect specific data from each company through which evaluate, once aggregated, for which Strategic Objective (SO) the potential aggregation is most suited. At this purpose a metric, consisting in a set of performance parameters related to different SO types, has been created. Given a large number of companies, through a genetic algorithm approach is then possible to set a specific objective function related to a particular SO (eg. maximize potential creation of new Business Opportunities), and to find the cluster (or clusters) of companies that maximizes the objective function.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
