SavedAdd your journal

Journals / Mathematical and Computational Applications / 2009 / Cilt: 14 - Sayı: 1

Simple and U-type assembly line balancing by using an Ant Colony based algorithm

ADİL BAYKASOĞLU
TÜRKAY DERELİ
Pages
1–12
DOI
—
🏛️Bibliographic metadata and full text access for this article are provided via DergiPark.
DergiPark Record ↗
✨

AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

The result of the computational study has shown that the proposed algorithm is effective in solving simple/U-shaped line balancing problems.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:In this paper, an Ant Colony Optimization (ACO) based heuristic algorithm is proposed for solving simple (straight line) and U-shaped assembly line balancing problems (ALBP).
📊
Key Findings & Data:A new algorithm is proposed in this paper that seamlessly integrates COMSOAL algorithm, Ranked Positional Weight Heuristic (RPWH) and an ACO based heuristic in order to obtain good solutions to simple and U-shaped ALBPs.
💡
Conclusion & Impact:The result of the computational study has shown that the proposed algorithm is effective in solving simple/U-shaped line balancing problems.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Domain Parameters

Abstract

In this paper, an Ant Colony Optimization (ACO) based heuristic algorithm is proposed for solving simple (straight line) and U-shaped assembly line balancing problems (ALBP). The paper makes one of the first attempts to show how ACO heuristic can be used to solve U-shaped ALBP. A new algorithm is proposed in this paper that seamlessly integrates COMSOAL algorithm, Ranked Positional Weight Heuristic (RPWH) and an ACO based heuristic in order to obtain good solutions to simple and U-shaped ALBPs. The result of the computational study has shown that the proposed algorithm is effective in solving simple/U-shaped line balancing problems.

🔖

Cite This Article

BAYKASOĞLU, A., DERELİ, T. (2009). Simple and U-type assembly line balancing by using an Ant Colony based algorithm. Mathematical and Computational Applications, Cilt: 14 - Sayı: 1, 1–12. https://ajindex.com/articles/280075

📄 Full Text PDF Viewer

📄

PDF görüntüleyici hazırlanıyor...

References (16)

  1. D.A. Ajenblit, R.L. Wainwright, Applying genetic algorithms to the U-shaped assembly line balancing problem. Proceedings of the 1998 IEEE International Conference on Evolutionary Computation, Anchorage, Alaska, pp. 96-101, 1998
  2. A.L. Arcus, COMSOAL: A computer method of sequencing operations for assembly lines, International Journal of Production Research 4, 259-277, 1966
  3. I. Baybars, A survey of exact algorithms for the simple assembly line balancing Problem, Management Science 32, 909-932, 1986
  4. F.F. Boctor, A multiple-rule heuristic for assembly line balancing, Journal of Operational Research Society 46, 62–69, 1995
  5. B. Bullnheimer, R.F. Hartl, C. Strauss, A new rank-based version of the ant system: a computational study, Central European Journal of Operations Research and Economics 7, 25-38, 1999
  6. K.C.C. Chan, P.C.L. Hui, K.W. Yeung, F.S.F. Ng, Handling the assembly line balancing problem in the clothing industry using a genetic algorithm, International Journal of Clothing Science and Technology 10, 21-37, 1998
  7. W-C. Chiang, The application of a tabu search metaheuristic to the assembly line balancing problem, Annals of Operations Research 77, 209-227, 1998
  8. A. Colorni, M. Dorigo, V. Maniezzo, M. Trubian, Ant system for job-shop Scheduling, JORBEL-Belgian Journal of Operations Research, Statistics and Computer Science 34, 39-53, 1994
  9. D. Costa, A. Hertz, Ants can color graphs, Journal of the Operational Research Society 48, 295-305, 1997
  10. M. Dorigo, V. Maniezzo, A. Colorni, Positive feedback as a search strategy, Technical Report, 91-016, Politecnico idi Milano, 1991
  11. M. Dorigo, Ottimizzazione, apprendimento automatico, ed algoritmi basati su metafora naturale (Optimization, Learning and Natural Algorithms), Ph.D.Thesis, Politecnico di Milano, Italy, in Italian, 1992
  12. M. Dorigo, V. Maniezzo, A., Colorni, The ant system: optimization by a colony of cooperating agents, IEEE Transactions on Systems, Man, and Cybernetics-Part B 26, 29-41, 1996
  13. M. Dorigo, G. Di Caro, L.M. Gambardella, Ant algorithms for discrete optimization, Artificial Life 5, 137-72, 1999
  14. M. Dorigo, E. Bonabeau, G. Theraulaz, Ant algorithm and stigmergy, Future Generation Computer Systems 16, 851-871, 2000
  15. E.A. Elsayed, T.O. Boucher, Analysis and Control of Production Systems, New Jersey: Prentice Hall, 1994
  16. E. Erel, I. Sabuncuoglu, B.A. Aksu, Balancing of U-type assembly systems using simulated annealing, Int. Journal of Producti