A novel time, cost, quality and risk tradeoff model with a knowledge-based hesitant fuzzy information: An R&D project application

•A novel approach for identifying the best implementation situation for each activity in a project.•Optimizing and balancing time, cost, quality, and risk criteria under uncertain circumstances via hesitant fuzzy linguistic term sets (HFLTs).•Model validation thru a real-world case study from an R&D project in the food industry. This paper proposes a novel approach for identifying the best implementation situation for each activity in a project by optimizing and balancing time, cost, quality, and risk criteria under uncertain circumstances. A hesitant fuzzy linguistic term set (HFLTS) approach is proposed to determine the status of project activities in the presence of quality and risk criteria alongside time and cost. Afterwards, a multi-objective linear programming (MOLP) model is formulated for time, cost, quality, and risk trade-off (TCQRT). To validate the model, a research and development project in the food industry is investigated. The results indicate that the project's time compared to the deterministic approach was reduced by 20%. Completing the R&D project earlier than other competitors brings a higher profit for the company than trade-off expenses, even without considering the quality and risk trade-off benefits of the proposed approach. Considering uncertainty in the risk and quality of activities in a project via HFLTSs and optimizing all four elements of time, cost, quality, and risk simultaneously are the main values of this research. The proposed approach can be employed by managers to adopt and optimize project planning and scheduling while optimizing the trade-offs among TCQR factors in uncertain circumstances.