Optimization of Quantitative and Qualitative Indicators of Construction Projects with a Project Management Knowledge Approach (Case study: Qucham Reservoir Dam)

In recent years, the complexity of project implementation, competitive business environment, and limited resources of organizations have shown the need to pay attention to project management in achieving project goals. Therefore, in the implementation process, employers seek to increase quality, reduce execution time, costs, and risk, which are their main goals. In this research, optimization between the components of the survival pyramid including time, cost, quality, and risk in construction projects are done on a case-by-case basis on the Qucham reservoir dam. For this purpose, six Metahioristic optimization algorithms are used, which are three classical algorithms (genetics, Tabu search, and simulated annealing) and three new algorithms (butterfly, cyclical parthenogenesis, and harris hawk). In four cases, each component of the survival pyramid is optimized separately, and finally, all four cases are examined simultaneously. Coding related to objective functions and optimization algorithms has been done in MATLAB software. The results indicate the proper performance of the genetic algorithm. Also, in optimizing the quality index, only the genetic algorithm has given the best optimal answer, and in the combined optimization, considering all the indicators simultaneously, the genetic algorithms and the Harris hawk have given the best solution.