Multi-objective simulation optimization for the process of R&D projects based on DSM

Process structure uncertainties in complex products R&D projects are analyzed. The R&D process is simulated and modeled with design structure matrix (DSM). DSM scheduling policies are used in the DSM simulation. We develop a multi-objective optimization model with the objective of minimizing both project duration and cost. We propose a hybrid algorithm based on DSM simulation and nondominated sorting genetic algorithm II to generate the Pareto-optimal solutions for our multi-objective optimization problem. The proposed hybrid algorithm is applied to a real-world R&D project process optimization problem. The results show that our hybrid algorithm is robust and valid. Moreover, a simulation is used to evaluate and analyze the resulting optimal project process structure.