This article exclusively formulates and presents three innovative hypotheses related to the execution of share buybacks, employing Genetic Algorithms (GAs) and mathematical optimization techniques. Drawing on the foundational contributions of scholars such as Osterrieder, Seigne, Masters, and...

The purpose of this study is to build a system that automatically generates an optimal strategy (AGOS) which can solve the business problem of maximizing the acceptance rate without taking more risks in loan approval process. This paper formulates the finding an optimal approval strategy of a...

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...

In this era of rapid digital revolution within the financial sector, our paper offers a cutting-edge approach to the intricacies of share buyback programs by employing Genetic Algorithms (GAs). Navigating the complexity of financial market operations, we leverage artificial intelligence to craft...

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 application of simulation modeling in public administration is under study at the level of interregional interaction in specific federal districts. The main indicator for development success of a particular federal district is the natural growth of its population. For this purpose, a model...

In this paper we consider, for the first time, the setup and travel times of cranes in the berth allocation and quay crane assignment problem. We first propose a new mixed integer linear programming model (MILP) for the problem without setups (BACASP), in which neither the berthing positions nor...

With the advent of Big Data, managing large-scale portfolios of thousands of securities is one of the most challenging tasks in the asset management industry. This study uses an evolutionary multi objective technique to solve large-scale portfolio optimisation problems with both long-term listed...