In this paper, a new multiobjective optimization framework based on nondominated sorting
and local search (NSLS) is introduced. The NSLS is based on iterations. At each iteration …

Multiobjective evolutionary algorithm based on decomposition (MOEA/D) and an improved
non-dominating sorting multiobjective genetic algorithm (NSGA-II) is two well known …

This paper reviews some state-of-the-art hybrid multiobjective evolutionary algorithms
(MOEAs) dealing with multiobjective optimization problem (MOP). The mathematical …

Evolutionary algorithms (EA s) have amply shown their promise in solving various search
and optimization problems for the past three decades. One of the hallmarks and niches of …

This book presents an overview of several archiving strategies we have developed over the
last years dealing with approximations of the solution sets of multi-objective optimization …

This chapter provides a short overview of the most significant research work that has been
conducted regarding the solution of computationally expensive multi-objective optimization …

Among numerous multi-objective optimization algorithms, the Elitist non-dominated sorting
genetic algorithm (NSGA-II) is one of the most popular methods due to its simplicity …

The optimization of parallel kinematic manipulators (PKM) involve several constraints that
are difficult to formalize, thus making optimal synthesis problem highly challenging. The …

List of References on Evolutionary Multiobjective Optimization Page 1 List of References on
Evolutionary Multiobjective Optimization Carlos A. Coello Coello ccoello@cs.cinvestav.mx …

Started during 1993-95 with three different algorithms, evolutionary multi-objective
optimization (EMO) has come a long way in a quick time to establish itself as a useful field of …