The paper "Development of time-cost trade-off optimization model for construction projects with MOPSO technique" by Aditya Kumar Agarwal, Shyamveer Singh Chauhan, Kamal Sharma, and Krushna Chandra Sethi addresses the critical challenge of balancing time and cost in construction project scheduling. The study introduces a multi-objective particle swarm optimization (MOPSO) technique to develop a time-cost trade-off (TCT) optimization model, focusing on multi-mode construction activities. Each mode represents different options for activities, requiring varying resources, time, and costs. The model aims to select the best alternatives for project activities, generating a set of Pareto-optimal solutions. The effectiveness of the MOPSO method is demonstrated through a real case study, comparing it with existing trade-off optimization methods. The research provides trade-off plots and an a priori approach to help project teams make informed decisions, ultimately maximizing profits and improving scheduling choices. The paper also reviews past research on project scheduling methods, including deterministic, heuristic, and meta-heuristic techniques, and discusses the concept of multi-mode activity execution and resource constraints.The paper "Development of time-cost trade-off optimization model for construction projects with MOPSO technique" by Aditya Kumar Agarwal, Shyamveer Singh Chauhan, Kamal Sharma, and Krushna Chandra Sethi addresses the critical challenge of balancing time and cost in construction project scheduling. The study introduces a multi-objective particle swarm optimization (MOPSO) technique to develop a time-cost trade-off (TCT) optimization model, focusing on multi-mode construction activities. Each mode represents different options for activities, requiring varying resources, time, and costs. The model aims to select the best alternatives for project activities, generating a set of Pareto-optimal solutions. The effectiveness of the MOPSO method is demonstrated through a real case study, comparing it with existing trade-off optimization methods. The research provides trade-off plots and an a priori approach to help project teams make informed decisions, ultimately maximizing profits and improving scheduling choices. The paper also reviews past research on project scheduling methods, including deterministic, heuristic, and meta-heuristic techniques, and discusses the concept of multi-mode activity execution and resource constraints.