In this paper, the concept of partial pseudo-triangular entropy as a superior measure of indeterminacy for uncertain random variables is proposed. It is first proved that partial entropy and partial triangular entropy sometimes fail to measure the indeterminacy of an uncertain random variable. Then, the concept of partial pseudo-triangular entropy and its mathematical properties are investigated. To illustrate the outperformance of partial pseudo-triangular entropy as a measure of risk, a portfolio optimization problem is optimized via different types of entropy. Furthermore, a genetic algorithm (GA) is implemented in MATLAB to solve the corresponding problem. Numerical results show that partial pseudo-triangular entropy as a quantifier of portfolio risk outperforms partial entropy and partial triangular entropy in the uncertain random portfolio optimization problem. Manuscript profile