A multiobjective optimization problem involves several conflicting objectives and has a set of
Pareto optimal solutions. By evolving a population of solutions, multiobjective evolutionary …

Multi-objective formulations are realistic models for many complex engineering optimization
problems. In many real-life problems, objectives under consideration conflict with each …

This paper presents a multi-objective version of the artificial vultures optimization algorithm
(AVOA) for a multi-objective optimization problem called a multi-objective AVOA (MOAVOA) …

Balancing convergence and diversity plays a key role in evolutionary multiobjective
optimization (EMO). Most current EMO algorithms perform well on problems with two or three …

Many different types of multi-objective optimization problems, eg multi-modal problems and
large-scale problems, have been solved with high performance by numbers of tailored multi …

It is commonly accepted that Pareto-based evolutionary multiobjective optimization (EMO)
algorithms encounter difficulties in dealing with many-objective problems. In these …

Partly due to lack of test problems, the impact of the Pareto set (PS) shapes on the
performance of evolutionary algorithms has not yet attracted much attention. This paper …

This paper proposes a multimodal multiobjective Differential Evolution optimization
algorithm (MMODE). The technique is conceived for deployment on problems with a Pareto …

To handle the multiobjective optimization problems of truss-bar design, this paper introduces
a new metaheuristic multiobjective optimization algorithm. The proposed algorithm is based …

Under mild conditions, it can be induced from the Karush-Kuhn-Tucker condition that the
Pareto set, in the decision space, of a continuous multiobjective optimization problem is a …