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A survey of simulated annealing applications to operations research problems

Author

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  • Koulamas, C
  • Antony, SR
  • Jaen, R

Abstract

This paper surveys the application of simulated annealing (SA) to operations research (OR) problems. It is concluded that SA has been applied to both traditional (like single machine, flowshop and jobshop scheduling, lot sizing, traveling salesman problems) and non-traditional (like graph coloring, number partitioning) OR areas. It is also concluded that SA is quite appropriate when the alternative solution method is based on enumeration. SA usually requires more computational resources in exchange for not being trapped in local optima.

Suggested Citation

  • Koulamas, C & Antony, SR & Jaen, R, 1994. "A survey of simulated annealing applications to operations research problems," Omega, Elsevier, vol. 22(1), pages 41-56, January.
    • Handle: RePEc:eee:jomega:v:22:y:1994:i:1:p:41-56
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    Cited by:

    1. Ciancio, Claudio & Laganà, Demetrio & Musmanno, Roberto & Santoro, Francesco, 2018. "An integrated algorithm for shift scheduling problems for local public transport companies," Omega, Elsevier, vol. 75(C), pages 139-153.
    2. Bozer, Yavuz A. & Wang, Chi-Tai, 2012. "A graph-pair representation and MIP-model-based heuristic for the unequal-area facility layout problem," European Journal of Operational Research, Elsevier, vol. 218(2), pages 382-391.
    3. Özcan, Ugur, 2010. "Balancing stochastic two-sided assembly lines: A chance-constrained, piecewise-linear, mixed integer program and a simulated annealing algorithm," European Journal of Operational Research, Elsevier, vol. 205(1), pages 81-97, August.
    4. Pablo Adasme & Ali Dehghan Firoozabadi, 2019. "Facility Location with Tree Topology and Radial Distance Constraints," Complexity, Hindawi, vol. 2019, pages 1-29, November.
    5. Zhengwen He & Nengmin Wang & Pengxiang Li, 2014. "Simulated annealing for financing cost distribution based project payment scheduling from a joint perspective," Annals of Operations Research, Springer, vol. 213(1), pages 203-220, February.
    6. Robinson, Powell & Narayanan, Arunachalam & Sahin, Funda, 2009. "Coordinated deterministic dynamic demand lot-sizing problem: A review of models and algorithms," Omega, Elsevier, vol. 37(1), pages 3-15, February.
    7. Chen, Mu-Chen, 2001. "Tolerance synthesis by neural learning and nonlinear programming," International Journal of Production Economics, Elsevier, vol. 70(1), pages 55-65, March.
    8. Hu, Qian & Lim, Andrew, 2014. "An iterative three-component heuristic for the team orienteering problem with time windows," European Journal of Operational Research, Elsevier, vol. 232(2), pages 276-286.
    9. Menz, Georg & Schlichting, André & Tang, Wenpin & Wu, Tianqi, 2022. "Ergodicity of the infinite swapping algorithm at low temperature," Stochastic Processes and their Applications, Elsevier, vol. 151(C), pages 519-552.
    10. Thi-Kien Dao & Tien-Szu Pan & Trong-The Nguyen & Jeng-Shyang Pan, 2018. "Parallel bat algorithm for optimizing makespan in job shop scheduling problems," Journal of Intelligent Manufacturing, Springer, vol. 29(2), pages 451-462, February.
    11. Marcus Randall & Graham McMahon & Stephen Sugden, 2002. "A Simulated Annealing Approach to Communication Network Design," Journal of Combinatorial Optimization, Springer, vol. 6(1), pages 55-65, March.
    12. Muppani (Muppant), Venkata Reddy & Adil, Gajendra Kumar, 2008. "Efficient formation of storage classes for warehouse storage location assignment: A simulated annealing approach," Omega, Elsevier, vol. 36(4), pages 609-618, August.
    13. Moritz Mühlenthaler & Rolf Wanka, 2016. "Fairness in academic course timetabling," Annals of Operations Research, Springer, vol. 239(1), pages 171-188, April.
    14. Krystel K. Castillo-Villar, 2014. "Metaheuristic Algorithms Applied to Bioenergy Supply Chain Problems: Theory, Review, Challenges, and Future," Energies, MDPI, vol. 7(11), pages 1-33, November.
    15. Saha, Subrata & Sarkar, Biswajit & Sarkar, Mitali, 2023. "Application of improved meta-heuristic algorithms for green preservation technology management to optimize dynamical investments and replenishment strategies," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 209(C), pages 426-450.
    16. Zejia Liu & Zigui Zhang & Peifeng Xie & Zibo Miao, 2022. "Design of Selective TPV Thermal Emitters Based on Bayesian Optimization Nesting Simulated Annealing," Energies, MDPI, vol. 16(1), pages 1-16, December.
    17. Zhi-Long Chen & Nicholas G. Hall, 2007. "Supply Chain Scheduling: Conflict and Cooperation in Assembly Systems," Operations Research, INFORMS, vol. 55(6), pages 1072-1089, December.
    18. Qingzhu Yao & Xiaoyan Zhu & Way Kuo, 2014. "A Birnbaum-importance based genetic local search algorithm for component assignment problems," Annals of Operations Research, Springer, vol. 212(1), pages 185-200, January.
    19. Yu, Bin & Yang, Zhong-Zhen & Yao, Baozhen, 2009. "An improved ant colony optimization for vehicle routing problem," European Journal of Operational Research, Elsevier, vol. 196(1), pages 171-176, July.
    20. Nahas, Nabil & Ait-Kadi, Daoud & Nourelfath, Mustapha, 2006. "A new approach for buffer allocation in unreliable production lines," International Journal of Production Economics, Elsevier, vol. 103(2), pages 873-881, October.
    21. P Chen & C-C Wu & W-C Lee, 2006. "A bi-criteria two-machine flowshop scheduling problem with a learning effect," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 57(9), pages 1113-1125, September.
    22. Alkhamis, Talal M. & Hasan, Merza & Ahmed, Mohamed A., 1998. "Simulated annealing for the unconstrained quadratic pseudo-Boolean function," European Journal of Operational Research, Elsevier, vol. 108(3), pages 641-652, August.
    23. F Altiparmak & I Karaoglan, 2008. "An adaptive tabu-simulated annealing for concave cost transportation problems," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 59(3), pages 331-341, March.

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