Integrated Decision Support System for Bridges at Conceptual Design Stage

Subjectivity is the main factor that affects the selection process of a bridge type at the conceptual design stage. Selecting the bridge type is generally influenced by many parameters. In most cases, these parameters are evaluated and assessed by engineers based on their own experience, knowledge and judgment. Therefore, in an attempt to provide some consistency and objectivity to the selection process, this paper proposes a methodology to develop a model that incorporates systematical procedures that can be used to avoid and limit the decision maker’s subjectivity. This methodology considers "machine technique", which is a branch of Artificial Intelligence (AI), as the core for the guideline engine of the proposed model, besides using Artificial Neural Network (ANN) modeling with its back-propagation algorithm to identify and select the utmost solution. Comprehensive evaluation of bridge characteristics and parameters that influence the final decision is implemented and considered in the proposed model. The model is applicable for both general and specific cases of bridge design. Its simplicity, user friendly and comprehension would help designers minimize the influence of human subjectivity while taking major decisions; automatically rank all possible alternatives and consider all factors that impact the decision process. The process is automatic and will require minimal user intervention.