Following decades of sustained improvement, metaheuristics are one of the great success
stories of optimization research. However, in order for research in metaheuristics to avoid …

Meta-heuristic algorithms are problem-solving methods which try to find good-enough
solutions to very hard optimization problems, at a reasonable computation time, where …

This paper presents a modular framework for meta-heuristic optimization of complex
optimization tasks by decomposing them into subtasks that may be designed and developed …

This paper performs an unprecedented comparative study of Metaheuristic optimization
frameworks. As criteria for comparison a set of 271 features grouped in 30 characteristics …

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 …

Metaheuristics has attained increasing interest for solving complex real-world problems.
This paper studies the principles and the state-of-the-art of metaheuristic methods for …

In service oriented scenarios, applications are created by composing atomic services and
exposing the resulting added value logic as a service. When several alternative service …

Many classical search and optimization algorithms are especially insufficient in solving very
hard large scale nonlinear problems with stringent constraints. Hence, computational …

Large-scale global optimization is a research subject that has attracted significant attention,
including both theoretical and practical studies, in recent years. In this sense, some of the …

This paper describes the Java Metaheuristics Search framework (JAMES, v1. 1): an object‐
oriented Java framework for discrete optimization using local search algorithms that exploits …