Project selection and scheduling with uncertain net income and investment cost

This paper discusses an R & D project selection and scheduling problem in which there are no historical data about the project parameter values. The net income and investment cost in the problem are given by experts' evaluations and treated as uncertain variables. The different interactions among projects and the flexibility of project beginning time are considered. A new cost overrun risk is employed and a new optimisation model for R & D project selection and scheduling problem is given. Furthermore, deterministic equivalents of the model are presented and a genetic algorithm is designed for solving the proposed problem. As an illustration, a numerical example is provided.

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