This article presents a review and a comparative analysis between frameworks for solving
optimization problems using metaheuristics. The aim is to identify both the desirable …

Search-Based Software Engineering (SBSE) has been successfully applied to automate a
wide range of software development activities. Nevertheless, in those software engineering …

This paper describes jMetalPy, an object-oriented Python-based framework for multi-
objective optimization with metaheuristic techniques. Building upon our experiences with the …

Web service based applications often invoke services provided by third-parties in their
workflow. The Quality of Service (QoS) provided by the invoked supplier can be expressed …

We present the Java General Evolutionary Algorithm (JGEA) framework, a modular Java
framework for experimenting with Evolutionary Computation (EC). We designed JGEA to be …

In machine learning, hyperparameter tuning is strongly useful to improve model
performance. In our research, we concentrate our attention on classifying imbalanced data …

An important issue in hypervolume-based evolutionary multi-objective optimization (EMO)
algorithms is the specification of a reference point for hypervolume calculation. However, its …

While working on a software specification, designers usually need to evaluate different
architectural alternatives to be sure that quality criteria are met. Even when these quality …

Real-world optimization problems involving multiple conflicting objectives are commonly
best solved using multi-objective optimization as this provides decision-makers with a family …

Although metaheuristics have been widely recognized as efficient techniques to solve real-
world optimization problems, implementing them from scratch remains difficult for domain …