Profit Optimization for Multi-construction Projects Using Artificial Intelligence: Fid-Bau Portal

Profit Optimization for Multi-construction Projects Using Artificial Intelligence

Abdelghany, Raneem / Khairy, Mayar M. / Soliman, Menna / Hosny, Ossama / Essawy, Yasmeen A. S. / Shiha, Ahmed

The construction sector has changed throughout time and is evolving, and this evolution has resulted in a rise in construction material waste that is hazardous to the environment. This could be managed by utilizing a company’s available resources (such materials can include excessive steel, formwork, paintings, and other materials that are already with the same specifications within the projects and are available in other projects within the company’s portfolio) in an effective way. Contractors’ planning for a successful performance across the company’s portfolio and increasing the profitability of their investments are a must. One-way contractors can do so is by establishing long-term methods to ensure cost-effective and sustainable solutions to available resources across their companies’ portfolios. This paper presents an optimization model utilizing the resources of a company across its different projects with the objective of maximizing profit. The paper goes on to advocate that the optimized solution achieves recognizable sustainable limits. This optimized solution also contributes to sustainability by reducing construction waste and increasing cash flow. The objective of this research is implemented through an artificial intelligence model to handle such excess resources within a company’s portfolio of projects and minimize construction waste, it models the process flow so that construction material waste is whittled down, and along with that, profitability is to be taken into consideration. There are many variables that have an influence on the decision to utilize resources for a specific project within the portfolio. This paper considers financial products and projects’ different contractual, unique natures in the optimization procedure. In a global market that is becoming more competitive, costly, and smaller, optimizing profit and retaining profitability are crucial. In this research, three projects in one portfolio of a construction company defined by user inputs are used to analyze the possible excess resources usage across them and re-distributing the company’s overall cash flow. Through the application of a genetic algorithm tool, this research successfully obtains a near-optimal profit by utilizing the distribution and usage of different resources across the running projects managed by a company, reducing the waste and minimizing cost incurred at different periods throughout the projects’ running time.