A core challenge ofMultiobjective Evolutionary Algorithms (MOEAs) is to attain evenly distributed Pareto optimal solutions along the Pareto front. In this paper, we propose a novel asymmetric Pareto-adaptive (apa) scheme for the identification of well distributed Pareto optimal solutions based on the geometrical characteristics of the Pareto front. The apa scheme applies to problem with symmetr...

In this paper we show empirical data from Internet traffic measurements. Collected measurements are analyzed for different protocols, such as TCP and UDP. We perform statistical analysis through the correlation coefficients, covariance, and self-similarity degree i.e. Hurst parameter. Our experimental studies captured traffic with Hurst parameter around 0.7-0.75, which is near half way between ...

Reconfiguration of a power distribution system consists in changing the functional links among its elements and represents one of the most important actions for the improvement of system performance in operation. In the last few years, some authors have proposed approaches based on Pareto optimality for problem formulation of reconfiguration, with active power losses and reliability indices as ...

A non-cooperative game theoretical approach for analyzing opportunistic spectrum access in cognitive radio environments is proposed. New concepts from computational game theory are applied to spectrum access analysis in order to extract rules of behaviour for an emerging environment. In order to assess opportunistic spectrum access scenarios of cognitive radios, two oligopoly game models are re...

Most of the derivative-free optimization (DFO) algorithms rely on a comparison function able to compare any pair of points with respect to a blackbox objective function. Recently, new dedicated derivative-free optimization algorithms have emerged to tackle multi-objective optimization problems and provide a Pareto front approximation to the user. This work aims at reusing single objective DFO a...

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...

This chapter reviews methods for the assessment and comparison of Pareto set approximations. Existing set quality measures from the literature are critically evaluated based on a number of orthogonal criteria, including invariance to scaling, monotonicity and computational effort. Statistical aspects of quality assessment are also considered in the chapter. Three main methods for the statistica...

1. Abstract Multiobjective genetic algorithms (MOGAs) have successfully been used on a wide range of real world problems. However, it is generally accepted that the performance of most state-of-the-art multiobjective genetic algorithms tend to perform poorly for problems with more than four objectives, termed many-objective problems. The contribution of this paper is a new approach for identify...

Abstract To confront climate change, decarbonization strategies must change the global economy. According to statements made as part of European Green Deal, maritime transport should also become drastically less polluting. As a result, price reflect impact it has on environment and health. In such framework, purpose this paper is suggest novel method for minimizing emissions from ships, based s...