Random Fuzzy Decision Models for Pharmaceutical R&D Project Investment under Uncertainty

  •  Changsheng Yi    
  •  Qiumei Jin    


This paper considers an optimal stopping decision problem for pharmaceutical R&D project investment withoutrivalry in random fuzzy environments. Specifically, the R&D process can be regarded as a jump diffusion processof scientific knowledge full of complexity. Every jump represents a scientific breakthrough or a new knowledgediscovery. In classical R&D literature, the inter-arrival times between jumps are generally assumed as randomvariables which are exponentially distributed. Here, the inter-arrival times are treated as random fuzzy variablesobserve arbitrary distributions. Furthermore, the termination time of the project is incorporated into the R&Dmodels as a decision variable by allowing the decision-maker to sell the obtained technology at any point oftime. Three types of project return performance (expected net return, -optimistic net return and return reliability)are proposed and a spectrum of random fuzzy programming models are established to model the different R&Dinvestment decision problems according to the decision-maker’s attitude. Considering the complexity of thesemodels, the random fuzzy simulation is designed to estimate the values of project return performance and thesimultaneous perturbation stochastic approximation (SPSA) algorithm is employed to solve the proposed models.Finally, the effectiveness of the hybrid algorithm and the applicability of these models are illustrated by somenumerical examples.

This work is licensed under a Creative Commons Attribution 4.0 License.
  • ISSN(Print): 1927-7032
  • ISSN(Online): 1927-7040
  • Started: 2012
  • Frequency: bimonthly

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