RESEARCH ON THE SEQUENTIAL QUADRATIC PROGRAMMING DIFFERENTIAL EVOLUTION, JAYA, AND JAYA'S EVOLUTIONARY ALGORITHM

Abstract

This study focuses on researching and comparing optimization algorithms such as Sequential Quadratic Programming, Differential Evolution, Jaya, and Jaya's evolutionary algorithm. Sequential Quadratic Programming is an optimization method based on mathematical programming, where constraints and objective functions are represented by convex and differentiable functions. Differential Evolution is a combinatorial evolutionary algorithm that utilizes genetic operators such as crossover and mutation to generate new generations of individuals. Jaya is an optimization algorithm based on continuous improvement of the population, where individuals are updated based on the current best solution. This study focuses on the specific application of the Jaya evolutionary algorithm (iJaya) compared to other algorithms and compares the performance of these algorithms in solving optimization problems through real-world examples of fiber orientation optimization in stiffened composite plates. Experiments on popular optimization problems and measure factors such as runtime, accuracy, and the ability to search for optimal solutions were conducted. The research results will provide an overview of the performance and advantages of each algorithm, thereby providing recommendations for selecting the appropriate algorithm for corresponding problems in the construction field.