Affiliation:
1. Saint Joseph's University, USA
Abstract
To make sound decisions, managers analyze data from multiple sources using different dimensions and eventually integrate the results of their analysis. This study proposes the design of a multi-attribute-decision-support-system that combines the analytical power of two different tools: data envelopment analysis (DEA) and particle swarm optimization (PSO), one of the major algorithms using swarm intelligence. DEA measures the relative efficiency of decision making units that use multiple inputs and outputs to provide non-objective measures without making any specific assumptions about data. On the other hand PSO's main strength lies in exploring the entire search space. This study proposes a modeling technique that jointly uses the two techniques to benefit from the two methodologies.
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