Completion of the activities within optimal time and cost plays a significant role in construction projects. Recently, project managers have to decrease the total durations and costs of the projects more than before due to the competitive environment. Mostly, decision makers usually seek different alternatives which reduce time and cost. As well as being one of the most major topics of construction management, this problem called time-cost trade-off (TCTO) which is extremely difficult to solve with traditional mathematical methods. In recent years, metaheuristic algorithms are outstanding methods in this field due to their flexible and adaptable structure. This paper presents a new algorithm called F-PSO which consists of hybridizing Firefly Algorithm (FA) with Particle Swarm Optimization (PSO). In this method, the problem is modelled with various execution modes to select the optimal one for each activity. The applicability and validity of the proposed method is confirmed by performing 18-activity project as a benchmark problem. Comparison of numerical results with different metaheuristic algorithms demonstrates the effectiveness and efficiency of F-PSO with regard to optimality of time and cost outcomes.