This paper presents a multiobjective optimization algorithm for solving tri-objective optimization problems with objectives of very different scales. As a version of the Multiobjective Evolutionary Algorithm based on Decomposition (MOEA/D), it adopts the Normal Boundary Intersection (NBI) based Tchebycheff approach to decompose a multiobjective optimization problem into a number of single objec...

In this paper‎, ‎we introduce and study some new single-valued gap functions for non-differentiable semi-infinite multiobjective optimization problems with locally Lipschitz data‎. ‎Since one of the fundamental properties of gap function for optimization problems is its abilities in characterizing the solutions of the problem in question‎, ‎then the essential properties of the newly introduced ...

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...

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...

We consider multiobjective shortest paths, a fundamental (NP-hard) problem in multiobjective optimization, where we are interested not in optimizing a single objective, but in finding a set of paths that captures the trade-off (the so-called Pareto curve) among several objectives in a digraph whose edges are associated with multidimensional cost vectors. We provide a new FPTAS for computing an ...