In this paper, two kinds of possibility distributions, namely, upper and lower possibility distributions are identi®ed to re ̄ect experts' knowledge in portfolio selection problems. Portfolio selection models based on these two kinds of distributions are formulated by quadratic programming problems. It can be said that a portfolio return based on the lower possibility distribution has smaller po...

Reinforcement learning algorithm has been successfully used in prediction and decision making [5,11]. The main contribution of this paper is to provide decision making using reinforcement learning approach to allocate resources optimally in stochastic conditions in a well known example; in the portfolio selection. The modern theories of portfolio selection consider some presumptions. But if the...

The business environment is full of uncertainty. Allocating the wealth among various asset classes may lower the risk of overall portfolio and increase the potential for more benefit over the long term. In this paper, we propose a mixed singlestage R&D projects and multi-stage securities portfolio selection model. Specifically, we present a bi-objective mixed-integer stochastic programming mode...