Complexity and variety of modern multiobjective optimisation problems result in the
emergence of numerous search techniques, from traditional mathematical programming to …

In the last decades, a large number of metrics has been proposed to compare the
performance of different evolutionary approaches in multi-objective optimization. This …

This paper describes jMetal, an object-oriented Java-based framework aimed at the
development, experimentation, and study of metaheuristics for solving multi-objective …

Software design is a process of trading off competing objectives. If the user objective space
is rich, then we should use optimizers that can fully exploit that richness. For example, this …

Most of the real-world optimization problems have multiple objectives to deal with. Satisfying
one objective at a time may lead to the huge deviation in other. Therefore, an efficient tool is …

In this article, an improved Archive-based Micro Genetic Algorithm (referred to as AMGA2)
for constrained multi-objective optimization is proposed. AMGA2 is designed to obtain fast …

In this paper, we propose a new evolutionary algorithm for multi-objective optimization. The
proposed algorithm benefits from the existing literature and borrows several concepts from …

Comparing various metaheuristics based on an equal number of objective function
evaluations has become standard practice. Many contemporary publications use a specific …

Ridesharing is considered as one of the promising solutions for dropping the consumption of
fuel and reducing the congestion in urban cities, hence reducing the environmental …

This article presents a rough-to-fine evolutionary multiobjective optimization algorithm based
on the decomposition for solving problems in which the solutions are initially far from the …