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

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 sets (HFLTs) approach is proposed to determine the status of project activities in the presence of quality and risk criteria alongside their time and cost. Afterwards, a multi-objective linear programming (MOLP) model is formulated for a time, cost, quality, and risk tradeoff (TCQRT). To validate the model, a research and development project in the food industry was 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 bring higher profit than tradeoff expenses, even without considering the quality and risk tradeoff benefits of the proposed approach. Considering uncertainty in risk and quality of activities via HFLTs and also optimizing all four elements of time, cost, quality, and risk simultaneously in a project are the main values of this research. The proposed approach can be employed by managers to adopt and optimize project planning and scheduling while trading off TCQR in uncertain circumstances.

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