Application of modified symbiotic organisms search (msos) algorithm hybrid with Bayesian optimization leveling (bol) algorithm to propose optimal resource cost options

This research addresses a critical issue in the construction industry, where high competition and project-specific challenges pose significant difficulties in cost management, particularly in the realm of construction resource expenses. To tackle this issue, the study introduces the use of the "Modified Symbiotic Organisms Search" (MSOS) algorithm. The aim is to optimize costs related to construction resources in building projects. However, to enhance effectiveness and broaden criteria for the most suitable choices, the research supplements the MSOS algorithm with Bayesian Optimization Leveling (BOL). BOL aids in selecting the optimal outcome across multiple criteria based on the achieved optimal cost after several iterations. The research will undergo testing on an actual construction project to evaluate and compare the performance of MSOS-BOL with other methods. Through this, the study aspires to provide significant contributions to understanding how to manage equipment costs in the challenging environment of the construction industry and offer a practical method for optimizing resource costs.