Mohammad Azım Eırgash, Yusuf Baltacı
The Modified Adaptive Weight Approach (MAWA) represents a straightforward method commonly applied to solve time–cost optimization problems. MAWA is a flexible and effective approach that can be applied to various multi-objective optimization problems, including time–cost optimization in construction projects. These algorithms operate on a population of potential solutions that are randomly initialized within the boundaries of the solution space. MAWA assigns uniform weight factors to all individuals in the population without accounting for their specific characteristics. However, each solution possesses unique fitness attributes relative to its position in the solution space. In this study, a multi-objective optimization model combining the Rao-3 algorithm with the MAWA is introduced to generate a set of Pareto-optimal solutions. Two construction project case studies, drawn from existing technical literature and comprising 81 to 146 activities, are analyzed to evaluate the effectiveness of the proposed MAWA-Rao-3 method. The results are benchmarked against those from previously established models that produced approximate Pareto fronts or near-optimal solutions. The findings demonstrate that the MAWA-Rao-3 algorithm performs efficiently in addressing time-cost trade-off problems within the field of construction engineering and management.