In today’s competitive environment, projects must be implemented at a lower cost and in less time, and resources must be used optimally. Therefore, project management and scheduling using an efficient tool is a necessity. Resource constraint project scheduling (RCPSP) is one of the most widely...

The stock market is a highly complex non-linear and chaotic system that is influenced by political, economic and psychological factors. Therefore, it seems very difficult to check this system. More scientific studies with an emphasis on the accurate identification of stock price behavior led to...

Inspired with the research, we present an enhanced Deep Neural Network (DNN) framework that combines Symbolic Genetic Algorithm (SGA) with Long-Short Term Memory (LSTM) in predicting the cross-sectional price returns using 245 fundamental indicators in China. The study addresses the challenges...

We develop and implement methods for determining whether relaxing sparsity constraints on portfolios improves the investment opportunity set for risk-averse investors. We formulate a new estimation procedure for sparse second-order stochastic spanning based on a greedy algorithm and Linear...