Considering reducing the airspace congestion and the flight delay simultaneously, this paper formulates the airway network flow assignment (ANFA) problem as a multiobjective optimization model and presents a new multiobjective optimization framework to solve it. Firstly, an effective multi-island parallel evolution algorithm with multiple evolution populations is employed to improve the optimiz...

In this chapter, we discuss the application of evolutionary multiobjective optimization (EMO) to association rule mining. Especially, we focus our attention on classification rule mining in a continuous feature space where the antecedent and consequent parts of each rule are an interval vector and a class label, respectively. First we explain evolutionary multiobjective classification rule mini...

Multiobjective Decision Support technology has matured to the point where new efforts should incorporate components of existing systems, rather than build everything from scratch. To help such efforts, the Java source code to a multiobjective decision support system called “The Facilitator” has been revised and released under the Mozilla Public License. This open source effort will be of intere...

This paper presents a hybridization of neural networks and multiobjective memetic optimization for an adaptive, robust, and perceptual data hiding method for colour images. The multiobjective optimization problem of a robust and perceptual image data hiding is introduced. In particular, trade-off factors in designing an optimal image data hiding to maximize the quality of watermarked images and...

Consider a multiobjective decision problem with uncertainty in the objective functions, given as set of scenarios. In single-criterion case, robust optimization methodology helps to identify solutions which remain feasible and good quality for all possible A well-known alternative method single-objective case is compare decisions under optimal benefit hindsight, i.e. minimize (possibly scaled) ...

In this paper a multiobjective optimal design method of interior permanent magnet synchronous motor ( IPMSM) for traction applications so as to maximize average torque and to minimize torque ripple has been presented. Based on train motion equations and physical properties of train, desired specifications such as steady state speed, rated output power, acceleration time and rated speed of tract...

Many water resources systems are characterized by multiple objectives. For multiobjective optimization, typically there can be no single optimal solution which can simultaneously satisfy all the goals, but rather a set of technologically efficient noninferior or Pareto optimal solutions exists. Generating those Pareto optimal solutions is a challenging task and often difficulties arise in using...

The importance of tuning a search algorithm for the specific features of the target search space has been known for quite some time. However, when dealing with multiobjective problems, there are several twists on the conventional notions of fitness landscapes. Multiobjective optimization problems provide additional difficulties for those seeking to study the properties of the search space. Howe...

This paper reviews some state-of-the-art hybrid multiobjective evolutionary algorithms (MOEAs) dealing with multiobjective optimization problem (MOP). The mathematical formulation of a MOP and some basic definition for tackling MOPs, including Pareto optimality, Pareto optimal set (PS), Pareto front (PF) are provided in Section 1. Section 2 presents a brief introduction to hybrid MOEAs.