Using Parametric Statistical Performance Measure for Quality Assessment of multiobjectuve Multistage Ant Colony Optimization system

Article Sidebar

PDF
Published: Sep 19, 2013

Main Article Content

Abd Allah A. Mousa
taif university,faculty of science, mathematics department

Abstract

This paper is focused on using parametric statistical test of the results in the field of population-based techniques.  It  proposes a Parametric Statistical test as a performance measure for quality assessment  for Multiobjectuve Multistage Ant Colony Optimization MM-ACO system that optimize a fuzzy multi-objective resource allocation problem (FM-RAP), where the experimental analysis on the performance of a proposed algorithm is a crucial and necessary task to carry out in this research.   Our approach has two characteristic features. Firstly, a set of nondominated solutions is obtained by exploring the optimal Pareto frontier using different cut level and subsequently, based on the parametric statistical test, performance measure for the quality assessment was implemented in order to establish the viability of our algorithm, and to compare the results obtained by running our algorithms with the results obtained from applying particle swarm optimization Furthermore, we provided an example of optimum utilization of human resources in reclamation of derelict land.

Downloads

Download data is not yet available.

Article Details

How to Cite
Mousa, A. A. A. (2013). Using Parametric Statistical Performance Measure for Quality Assessment of multiobjectuve Multistage Ant Colony Optimization system. Journal of Global Research in Mathematical Archives(JGRMA), 1(7), 1–12. Retrieved from https://jgrma.com/index.php/jgrma/article/view/82
Issue
Vol. 1 No. 7 (2013): July-2013
Section
Research Paper
Download Copyright

References

Osman M.S., M.A.Abo-Sinna, and A.A. Mousa " IT-CEMOP: An Iterative Co-evolutionary Algorithm for Multiobjective Optimization Problem with Nonlinear Constraints" Journal of Applied Mathematics & Computation (AMC) 183, pp373-389, (2006)

M.S.Osman , M.A.Abo-Sinna , and A.A. Mousa " An Effective Genetic Algorithm Approach to Multiobjective Resource Allocation Problems ( MORAPs) " Journal Of Applied Mathematics & Computation (AMC) Vol 163. No. (2), 2005.

A.A. Mousa, (2010) 'Using genetic algorithm and TOPSIS technique for multiobjective transportation problem: a hybrid approach', International Journal of Computer Mathematics, 87: 13, 3017 -3029.

A.A.Mousa , M. A. El-Shorbagy , Waiel. F. Abd El-Wahed, Local search based hybrid particle swarm optimization for multiobjective optimization, International journal of Swarm and evolutionary computation, 3(2012),1:14.

A.A.Mousa , I.M.El_Desoky , Stability of Pareto optimal Allocation of Land eclamation by Multistage Decision-based Multipheromone Ant Colony Optimization, International journal of Swarm and evolutionary computation (2013), http://dx.doi.org/10.1016/j.swevo.2013.06.003i

M. Gen, R. Cheng, Genetic Algorithms and Engineering Optimization, John Wiley & Sons, Inc., New York, 2000.

S. Kirkpatrick, C. Gelatt, , M.. Vecchi, Optimization by simulated annealing, Science 220 ,671–680, 1983.

F. Glover Tabu search – Part I, ORSA Journal of Computing 1 ,190–206,1989.

Waiel. F. Abd El-Wahed, A.A.Mousa , M. A. El-Shorbagy, Integrating particle swarm optimization with genetic algorithms for solving nonlinear optimization problems, Journal of Computational and Applied Mathematics 235 (2011) 1446–1453.

A. A. Mousa , R. M. Rizk-Allah, W. .F. Abd El-Wahed, A hybrid ant colony optimization approach based local search scheme formultiobjective design optimizations, Electric Power Systems Research,81(2011)1014-1023.

O. Baskan, Soner. Haldenbilen, H. Ceylan, H. Ceylan, A new solution algorithm for improving performance of ant colony optimization Applied Mathematics and Computation, Volume 211, Issue 1, 75-84, 2009.

S.K. Chaharsooghi, Amir H. Meimand Kermani , An effective ant colony optimization algorithm (ACO) for multi-objective resource allocation problem (MORAP) Applied Mathematics and Computation, Volume 200, Issue 1, ,167-177, 2008.

Jelel euchi,rafaa mraihi, the urban bus routing problem in the Tunisian case by the hybrid artificial ant colony algorithm, International journal of Swarm and evolutionary computation, 2(2012),15:24.

J. Yang, Y. Zhuang ,An improved ant colony optimization algorithm for solving a complex combinatorial optimization problem, Applied Soft Computing, Volume 10, Issue 2, 653-660, 2010.

W. .F. Abd El-Wahed, A.A.Mousa , R. M. Rizk-Allah, A Hybrid Ant Colony Optimization Approach for Solving Multiobjective Design Optimization of Air-Cored Solenoid, The Online Journal on Power and Energy Engineering (OJPEE), Vol. 1 No. 4, October 2010.

M. Dorigo, L. Gambardella, Ant colony system: a cooperative learning approach to the traveling salesman problem, IEEE Transaction on Evolutionary Computation 1, 53–66, 1997.

V. Maniezzo, A. Colorni, M. Dorigo, The ant system applied to the quadratic assignment problem, Universite Libre de Bruxelles, Belgium, Technical Report IRIDIA/94-28,1994.

S.J. Shyu, P.Y. Yin, B.M.T. Lin, T.S. Hsiao . An ant colony optimization algorithm for the minimum weight vertex cover problem, Annals of Operations Research 131,283–304,2004.

P.Y. Yin, Ant colony search algorithm for optimal polygonal approximation of plane curves, Pattern Recognition 36 ,1783–1797, 2003.

Dorigo M., Stuzle T. Ant Colony Optimization, MIT Press, Cambridge, MA,2004.

. Iredi, D. Merkle, M. Middendorf, Bi-Criterion Optimization with Multi Colony Ant Algorithms, First International Conference on Evolutionary Multi-criterion Optimization (EMO’01), vol. 1993, Lecture Notes in Computer Science, 2001, p. 359-372.

W. F. Abd El-Wahed, A. A. Mousa and R. M. Rizk-Allah, â€Reclamation Of Derelict Land In Toshka-Egypt By Multistage Decision-Based Multipheromone Ant Colony Optimization “,Al- Azhar Engineering Tenth international conference ,December 24 - 26, 2008.