Amirkabir University of Technology Amirkabir Journal of Civil Engineering 2588-297X 52 5 2020 07 22 Developing a Hybrid Optimization Scheduling Model in Construction Projects Using Comparative Analysis of Existing Meta-heuristic Algorithms Developing a Hybrid Optimization Scheduling Model in Construction Projects Using Comparative Analysis of Existing Meta-heuristic Algorithms 1221 1242 3298 10.22060/ceej.2019.15163.5874 FA Shayan Nikoukar School of civil engineering, College of engineering faculty, University of Tehran, Tehran, Iran 0009-0000-6613-8641 Journal Article 2018 11 14 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 the importance of clever 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 algorithm to solve a multi-objective optimization problem in construction project planning and finance. Because of the ability to get out of local optimization points, meta-algorithms can provide satisfactory results in complex problems in a short time. 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 the 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 acceptable processing time. 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 the importance of clever 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 algorithm to solve a multi-objective optimization problem in construction project planning and finance. Because of the ability to get out of local optimization points, meta-algorithms can provide satisfactory results in complex problems in a short time. 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 the 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 acceptable processing time. https://ceej.aut.ac.ir/article_3298_fa84632d742f2729dc32ce8cb5d49733.pdf