Buradasınız

ENDÜSTRİYEL PROBLEMLERİN ÇÖZÜMÜNDE DAĞINIK ARAMA YÖNTEMİ: LİTERATÜR ARAŞTIRMASI

SCATTER SEARCH METHOD FOR SOLVING INDUSTRIAL PROBLEMS: LITERATURE SURVEY

Journal Name:

Publication Year:

Abstract (2. Language): 
The evolutionary approach called scatter search is originated from strategies for creating composite decision rules and surrogate constraints. Recent studies demonstrate the practical advantages of these approaches. Scatter search method have recently been investigated optimization technique and alternative of the other Meta heuristic methods. The scatter search is an evolutionary search method whose principles were introduced in the early 1970. Before the 1990 there weren’t enough studies in the literature. Due to recent successful application of scatter search, there have been intensive researches in the literature. In this paper we demonstrate the procedure of scatter search and steps of method for application industrial problems. The goal of this paper is a literature survey of recent applications of scatter search methods on industrial problems.
Abstract (Original Language): 
Evrimsel bir yaklaşım olan dağınık arama metodu kompozit karar kurallarını ve kısıtları üreten stratejilerden oluşur. Bugüne kadar yapılan çalışmalar incelenen yaklaşımın avantajlarını göstermiştir. Dağınık arama metodu oldukça yeni bir optimizasyon tekniğidir ve diğer evrimsel tekniklere rakip durumundadır. Dağınık arama yöntemi, 1970’lerin başında prensipleri belirlenen evrimsel bir arama metodudur. 1990’lı yılların öncesinde bu yöntem üzerinde fazla durulmamıştır. Özellikle son on yılda dağınık arama yöntemine ilgi artmış ve bu yönde çalışmalar yoğunlaşmıştır. Bu çalışmada, dağınık arama yöntemi izah edilmiş ve endüstriyel problemlerde uygulama adımları belirlenmiştir. Bu araştırmada, dağınık arama metodunun, endüstriyel problemler üzerinde son yıllardaki uygulamalarının, literatür taraması yapılmıştır. Ayrıca araştırmada, dağınık arama yönteminin endüstriyel problemlerde uygulanması ile elde edilen katkılar detaylı olarak izah edilmiştir.
144-155

REFERENCES

References: 

[1] Sağıroğlu, Ş., Beşdok, E., Erler, M. 2003. Mühendislikte Yapay Zeka Uygulamaları-I:
Yapay Sinir Ağları, Ufuk Yayıncılık, Kayseri.
[2] Russell, S., Norvıg, P. 1995. Artificial Intelligence- A Modern Approach, Prentice Hall,
Int. Ed.
[3] Zahedı, F. 1993. Intelligent Systems for Business, Expert Systems With Neural Networks,
Wadsworth, USA
[4] Anonim, 2003a. Yapay Zeka Araştırma Alanları ve 21. Yüzyılda Yapay Zeka,
www.yapay-zeka.org [erişilme tarihi Ağustos 2005].
[5] Lourenço, H., Marti, R., Laguna, M. 2000. Assigning Proctors to Exams with Scatter
Search. In Computing Tools for Modeling, Optimization and Simulation: Interfaces in
Computer Science and Operations Research, M. Laguna and J. L. González-Velarde, Eds.
Kluwer Academic Publishers, Boston, MA, 215--227.
[6] Fleurent, C., Glover, F., Michelon, P., Vali, Z. 1996. A Scatter Search Approach for
Unconstrained Continuous Optimization. IEEE. 0-7803-2902-3.
[7] Sagarna, R., Lozano, J. A. 2006. Scatter Search in Software Testing, Comparison and
Collaboration with Estimation of Distribution Algorithms. European Journal of
Operational Research. Vol.169. 392-412.
[8] Vasconcelas, J.A., Maciel, J.H.R.D., Parreiras, R.O. 2005. Scatter Search Techniques
Applied to Electromagnetic Problems. IEEE Transactions On Magnetics. Vol 41.no 5.
[9] Cano, D.B., Santana, J.B., Rodriguez, C.C., Del Amo, I.J.G., Torres, M.G., Garcia,
F.J.M., Batista, B.M., Perez, J.A.M., Vega, J.M.M., Martin, R.R. 2004. Nature-inspired
Components of the Scatter Search. Technical Report.
[10] Garcia, F., Melian, B., Moreno, J.A., Moreno-Vega, J.M. 2002. Scatter Search for
Multiple Objective p-facility Location Problems.
http://www.lifl.fr/PM2O/Reunions/04112002/garcia.pdf [erişilme tarihi Ağustos 2005].
[11] Russell, R.A.,Chiang W.C. 2006. Scatter Search for the Vehicle Routing Problem With
Time Windows. European Journal of Operational Research. Vol.169. 606-622.
[12] Greistorfer, P. 2002. A Tabu Scatter Search Metaheuristic for the Arc Routing Problem.
Elsevier Science.
[13] Silva, C.G.D., Climaco, J., Figueira, J. 2006. A Scatter Search Method for Bi-criteria
{0,1}-Knapsack Problems, European Journal of Operational Research. Vol 169. 373-391.
[14] Diaz, B.A., Corbajal, S.G., Lozano, S. 2006. An Empirical Investigation on Parallelization
Strategies for Scatter Search. European Journal of Operational Research. Vol.169. 490-
507.
[15] Silva, C.G.D., Climaco, J., Figueira, J. 2003. A Scatter Search Method For The Bi-criteria
Multi-dimensional {0,1}-Knapsack Problem Using Surrogate Relaxation. Journal of
Mathematical Modelling and Algorithms, forthcoming.
[16] Nowicki, E., Smutnicki, C. 2006. Some Aspects of Scatter Search in the Flow-Shop
Problem. European Journal of Operational Research. Vol.169. 654-666.
[17] Yamashita, D.S., Armentano, V.A., Laguna, M. 2006. Scatter Search for Project
Scheduling with Resource Availability Cost.European Journal of Operational Research.
623-637.
[18] Debels, D., Reyck, B.D., Leus, R., Vanhoucke, M. 2003. A Hybrid Scatter Search /
Electromagnetism Meta-heuristic for Project Scheduling. Vlerick Leuven Gent Working
Paper Series. 25.
[19] Beausoleil, R.P. 2006. “MOSS” Multiobjective Scatter Search Applied to Non-linear
Multiple Criteria Optimization. European Journal of Operational Research. Vol.169. 426-
449.
[20] Ugray, Z., Lasdon, L., Plummer, J., Kelly, J. 2003. OQNLP: A Scatter Search Multistart
Approach for Solving Constrained Non-linear Global Optimization Problems. 3rd Annual
McMaster Optimization Conference: Theory and Applications (MOPTA 03).Hamilton,
Ontario.
[21] Cordan, O., Damas, S., Santamaria, J. 2002. A Scatter Search Algorithm for the 3D Image
Registration Problem.
[22] Scheuerer, S., Wendolsky, R. 2006. A Scatter Search Heuristic For The Capacitated
Clustering Problem.European Journal of Operational Research. Vol.169. 533-547.
[23] Lopez, F.G., Torres, M.G., Batista, B.M., Perez, J.A.M., Vega, J.M.M. 2006. Solving
Feature Subset Selection Problem by a Paralel Scatter Search. European Journal of
Operational Research. Vol.169. 477-489.
[24] Herrera, F., Lozano, M., Molina, D. 2006. Continuous Scatter Search: An analysis of the
integration of some combination methods and improvement strategies. European Journal
of Operational Research. Vol. 169. 450-476.
[25] Coleman, R. 2005. Single-Parameter Blackjack Betting Systems Inspired by Scatter
Search. Proceedings of the International Conference on Information Technology : Coding
and Computing. 7695-2315-3.
[26] Blazewicz, J., Glover, F., Kasprzak, M. 2004. DNA Sequencing- Tabu and Scatter Search
Combined. Informs Journal on Computing. Vol 16. No 3. 232-240.
[27] Sampson, P.O.D., Şahin, F. 2004. Structural Learning of Bayesian Networks from
Complete Data Using the Scatter Search Documents. IEEE International Conference On
Systems, Man and Cybernetics. 7803-8566-7.
[28] Hung, W.N.N., Song, X., Aboulhamid, E.M., Driscoll, M.A. 2002. BDD Minimization by
Scatter Search. IEEE Transactions On Computer-Aided Design of Integrated Circuits and
Systems. Vol 21. no 8.
[29] Sevaux, M., Thomin, P. 2002. Scatter Search and Genetic Algorithm: a one machine
scheduling problem comparison. The sixteenth triennial conference of international
federation of operational research societies, IFORS, Edinburgh, UK, juillet.
[30] Hung, W.N.N., Song, X. 2001. BDD Variable Ordering by Scatter Search. IEEE. 0-7695-
1200-3.

Thank you for copying data from http://www.arastirmax.com