Enhanced Multi-objective Evolutionary Algorithms Using Local Dominance

نویسندگان

  • Hiroyuki Sato
  • Hernán E. Aguirre
  • Kiyoshi Tanaka
چکیده

In this paper, we propose a calculation method of local dominance and enhance multiobjective evolutionary algorithms by performing a distributed search based on local dominance. We divide the population into several sub-populations by using declination angles of polar coordinate vectors in the objective space. We calculate local dominance for individuals belonging to each sub-population based on the local search direction, and apply genetic operators to individuals within each sub-population. We verify the effectiveness of the proposed method by comparing the search performance between NSGA-II, SPEA2 and their enhanced versions.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

A New Multi-objective Job Shop Scheduling with Setup Times Using a Hybrid Genetic Algorithm

This paper  presents a new multi objective job shop scheduling with sequence-dependent setup times. The objectives are to minimize the makespan and sum of the earliness and tardiness of jobs in a time window. A mixed integer programming model is developed for the given problem that belongs to NP-hard class. In this case, traditional approaches cannot reach to an optimal solution in a reasonable...

متن کامل

Approximate Pareto Optimal Solutions of Multi objective Optimal Control Problems by Evolutionary Algorithms

In this paper an approach based on evolutionary algorithms to find Pareto optimal pair of state and control for multi-objective optimal control problems (MOOCP)'s is introduced‎. ‎In this approach‎, ‎first a discretized form of the time-control space is considered and then‎, ‎a piecewise linear control and a piecewise linear trajectory are obtained from the discretized time-control space using ...

متن کامل

A Bi-objective Stochastic Optimization Model for Humanitarian Relief Chain by Using Evolutionary Algorithms

Due to the increasing amount of natural disasters such as earthquakes and floods and unnatural disasters such as war and terrorist attacks, Humanitarian Relief Chain (HRC) is taken into consideration of most countries. Besides, this paper aims to contribute humanitarian relief chains under uncertainty. In this paper, we address a humanitarian logistics network design problem including local dis...

متن کامل

A Hybrid Algorithm using Firefly, Genetic, and Local Search Algorithms

In this paper, a hybrid multi-objective algorithm consisting of features of genetic and firefly algorithms is presented. The algorithm starts with a set of fireflies (particles) that are randomly distributed in the solution space; these particles converge to the optimal solution of the problem during the evolutionary stages. Then, a local search plan is presented and implemented for searching s...

متن کامل

Evolutionary Algorithms Based on Decomposition and Indicator Functions: State-of-the-art Survey

In the last two decades, multiobjective optimization has become mainstream because of its wide applicability in a variety of areas such engineering, management, the military and other fields. Multi-Objective Evolutionary Algorithms (MOEAs) play a dominant role in solving problems with multiple conflicting objective functions. They aim at finding a set of representative Pareto optimal solutions ...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2004