Building a Genetic Algorithm-Based and BIM-Based 5D Time and Cost Optimization Model

Abstract

The digitalization of data has recently had an impact on the building industry. Building information modeling (BIM) is a highly developed technology that is used to predict the cost, lifespan, energy use, and efficiency of buildings. To enhance the BIM accuracy of cost and time estimation currently, it’s easier than before by Using evolutionary algorithms (EA), which include contemporary algorithms like evolutionary strategies (ES), evolutionary programming (EP), particle swarm optimization (PSO), differential evolution (DE), and genetic algorithms (GA), the integration of artificial intelligence (AI). This study uses a code (plugin) created by GA and integrated into the BIM-5D model via Navisworks as a plugin to reduce the overall time and cost of construction projects. The plugin code, developed with Microsoft Visual Studio and the C# programming language, is an interface that enhances the accuracy of time and cost during construction stages with various five project time scenarios. The study’s findings indicate that the suggested plugin reduces project time by roughly 20% while also saving various amounts of money.