Developing an optimization financing cost-scheduling trade-off model in construction project

Abstract

Time-cost trade-off analysis is one of the most challenging tasks of construction project planners. Project planners face complicated multivariate time-cost optimization problems that require simultaneous minimization of total project duration and total project cost while considering issues related to the optimal present value of profit. In addition, given the complexity of construction projects in recent years, clever management has become increasingly important in cases of project financing and scheduling. There are choices and limits that make it difficult for project planners to develop a proper financing plan considering project time status. Therefore, the methods of financing affect the project plan. Parameters such as interest rate, contract terms, and financing options (i.e., types of the loan) in the project construction period can change the final profit value of the project. Hence, 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 financing. The main objective of the model is to present a Pareto chart that shows the trade-off between duration of the project and the financing cost by considering different durations for each activity of the project and various financing options. The model is first validated in a simple case study and then applied to a large-scale case study. The model shows the optimal solutions which have time and financing cost. For each optimal solution, the model will create a cash flow containing project (direct and indirect cost and payments) and financing flows (borrowed money and repayments of principal and interest) based on a work schedule. Finally, a sensitivity analysis is performed to examine the effects of changes in the various parameters of the project cash flow on the ultimate results. It is shown that the proposed model is superior to the existing models in finding better project planning solutions with lower total project duration and lower total project financing cost in the proposed construction project financing problems. In addition, the proposed model improves the solutions through generations and provides optimal solutions in acceptable processing time.

Keywords:

• Financing cost
• hybrid meta-heuristic algorithm
• cash flow
• scheduling
• multi-objective optimization
• large-scale project

Disclosure statement

No potential conflict of interest was reported by the authors.