Civil Engineering Project Management based on Improved Particle Swarm Optimization Algorithm

Recently, project management system aims to present the most recent advancements in design optimization of metaheuristic models in civil engineering. But achieving maximum efficiency is the challenging task that must be completed in order to ensure project success, save costs, and meet deadlines. In order to address the issues, this research presented Improved Particle Swarm Optimization Algorithm (IPSOA), which effectively reduces costs while resolving challenging scheduling constraints for optimization projects. Sensors are initially placed and employed in the development and building of contacts to get more basic information in order to properly identify structural faults. Then, automated operational procedures are used to collect real-time data on construction activities for the purpose of enhancing procedural operations evaluation and monitoring. With automated project tracking, the physical quantities of work completed on-site are effectively measured. Hence, the deterioration in structure is detected and constraint-based optimization issues are solved using the proposed IPSOA. The results demonstrated that with a Resource Utilization Ratio (RUR) of 98.21% the suggested IPSOA method outperformed existing models such as Passive - Radio Frequency Identification (P-RFID), Project Management Information System (PMIS) and Project Management Body of Knowledge (PMBOK) respectively.