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A Hybrid Parallel Multi-Objective Genetic Algorithm: HybJacIsCone Model

by Mahendra Kumar Gourisaria, B. S. P. Mishra, Satchidananda Dehuri
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 66 - Number 7
Year of Publication: 2013
Authors: Mahendra Kumar Gourisaria, B. S. P. Mishra, Satchidananda Dehuri
10.5120/11093-5576

Mahendra Kumar Gourisaria, B. S. P. Mishra, Satchidananda Dehuri . A Hybrid Parallel Multi-Objective Genetic Algorithm: HybJacIsCone Model. International Journal of Computer Applications. 66, 7 ( March 2013), 1-6. DOI=10.5120/11093-5576

@article{ 10.5120/11093-5576,
author = { Mahendra Kumar Gourisaria, B. S. P. Mishra, Satchidananda Dehuri },
title = { A Hybrid Parallel Multi-Objective Genetic Algorithm: HybJacIsCone Model },
journal = { International Journal of Computer Applications },
issue_date = { March 2013 },
volume = { 66 },
number = { 7 },
month = { March },
year = { 2013 },
issn = { 0975-8887 },
pages = { 1-6 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume66/number7/11093-5576/ },
doi = { 10.5120/11093-5576 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:21:41.745046+05:30
%A Mahendra Kumar Gourisaria
%A B. S. P. Mishra
%A Satchidananda Dehuri
%T A Hybrid Parallel Multi-Objective Genetic Algorithm: HybJacIsCone Model
%J International Journal of Computer Applications
%@ 0975-8887
%V 66
%N 7
%P 1-6
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In real world most of the optimization problems are multi-objective in nature. These problems take large amount of time to congregate to the true Pareto front. So the basic algorithm like non parallel NSGA II may not able to solve such problem in ?-tolerable amount of time. This paper proposes a new hybrid parallel multi-objective genetic algorithm and solve one of the real life problem i. e. , 0/1 knapsack problem. The proposed model is designed by combining the characteristics of Island model, Jakobovic model and Cone Separation model. It is experimented over a multi-core system and gives promising result over all the existing basic models in terms of converging to the true Pareto front.

References
  1. T. Al-Somani and K. Qureshi. Reliability Optimization Using Genetics Algorithms. Msc thesis, Saudi Arabia, King Abdul Aziz University. 2000
  2. J. Branke, T. Kaubler, and H. Schmeck. Guidance in evolutionary multiobjective optimization. , Advances in Engineering Software, volume 32(6), pages 499-508,2001
  3. J. Branke, H. Schmeck, K. Deb, and R. S. Maheshwar. Parallelizing multi-objective evolutionary algorithms: Cone separation. In Congress on Evolutionary Computation (CEC 2004), pages 1952-1957, Portland, Oregon, USA, 2004. IEEE Press
  4. E. Cantu-Paz. A survey of parallel genetic algorithms. Calculateurs Paralleles, volume 10(2), pages 141-171, 1998
  5. ] K. Deb, S. Agarwal, A. Pratap, and T. Meyarivan. A fast elitist non-dominated sorting genetic algorithm for multi-objective optimization: NSGA-II. In Proceedings of the 6th International Conference on Parallel Problem Solving from Nature, pages 849-858. Springer-Verlag, 2000.
  6. K. Deb, P. Zope, and A. Jain. Distributed computing of pareto-optimal solutions with evolutionary algorithm. In C. M. Fonseca, P. J. Fleming, E. Zitzler, K. Deb, and L. Thiele, editors, Evolutionary Multi-Criterion Optimization, LNCS, volume 2632, pages 534-549. Springer, 2003
  7. M. J. Flynn and Kevin W. Rudd. Parallel architectures. ACM Comput. Survey ,volume 28, pages 67-70, March 1996.
  8. E. E. Johnson. Completing an mimd multiprocessor taxonomy. SIGARCH Computer Architecture News, volume 16(3), pages 47-44, 1988.
  9. ] F. Streichert, H. Ulmer, and A. Zell. Parallelization of multi-objective evolutionary algorithms using clus¬tering algorithms. Evolutionary Multi-Criterion Opti¬mization, volume 3410, pages 92-107, 2005
  10. ] A. S. Tanenbaum and M. van Steen. Distributed Systems: Principals and Paradigms. Prentice Hall, Upper Saddle River, 2002
  11. D. A. van Veldhuizen. Considerations in engineering parallel multiobjective evolutionary algorithms. IEEE Transactions on Evolutionary Computation, volume 7(2), pages 144-173, 2003
  12. E. Zitzler, K. Deb, and L. Thiele. Comparison of multi-objective evolutionary algorithms: Empirical results. Technical report, INSTITUTION Swiss Federal Institute of Technology (ETH), Zurich, 1999
Index Terms

Computer Science
Information Sciences

Keywords

Parallel Multi-Objective Genetic Algorithm Trigger Model NSGA-II Cone Separation Model Island Model 0/1 Knapsack Problem HybJacIsCone Model

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