A Mathematical Model to Predict Optimal Risk Response Budget using Genetic Algorithm

Abstract

Construction projects encounter a variety of risks, which require a thorough risk response phase to identify, evaluate, and determine solutions. This study presents a methodology for effectively choosing an appropriate risk response strategy and allocating suitable funds for the risk response phase of building projects. The framework employs optimization approaches and evolutionary principles, specifically utilizing the Genetic Algorithm technique. The objective of the model is to reduce costs and determine a suitable fund allocation strategy with minimum risk. The effectiveness of the framework is assessed in an actual building project involving a ventilation and air conditioning system, demonstrating its ability to optimize risk response and assist decision-makers in making well-informed choices.