Developing a hybrid optimization scheduling model in construction projects using comparative analysis of existing meta-heuristic algorithms

Time-cost trade-off analysis is one of the most challenging tasks of construction project planners. Project planners face complicated multivariate, Time-Cost Optimization (TCO) problems, which require simultaneous minimization of total project duration and total project cost, while considering issues related to the optimal present value of profit. Also, the complexity of construction projects in recent years has risen up the importance of cleverly management in cases of project financing and scheduling. There are choices and limits that make it difficult to project planners to develop a proper financing plan considering project time status. Therefore, the methods of financing affect the project plan. Therefore, a skilled planner should consider various effective parameters for scheduling projects. This study presents a hybrid meta-heuristic algorithms to solve a multi-objective optimization problem in construction project planning and finance. First, the model is compared with common meta-heuristic algorithms in a simple case study. Then it is applied to a complex case study and it shows the optimal solutions which have time, cost and net present value of profit. It is shown that the proposed model is superior to the existing optimization algorithms to find better project planning solutions with less total project duration, less total project cost, and optimal profit in the construction project problems. The cumulative results are shown in a three-dimensional Pareto front. Also, the proposed model improves the solutions through generations and provide optimal solutions in an acceptable processing time.