Simulated annealing (SA) algorithm is a probabilistic optimization
technique inspired by the annealing process in metallurgy, where a
material is heated and then slowly cooled to reach a low-energy
configuration. The main idea behind the algorithm is to explore
the solution space and gradually converge to an optimal solution,
similar to how a material gradually settles into a stable configuration
during cooling.
References
- Aarts, E. H., & Van Laarhoven, P. J. (1987). Simulated annealing: a pedestrian review of the theory and some applications. In Pattern recognition theory and applications (pp. 179-192). Berlin, Heidelberg: Springer Berlin Heidelberg.
- Koulamas, C., Antony, S. R., & Jaen, R. (1994). A survey of simulated annealing applications to operations research problems. Omega, 22(1), 41-56.
- Suman, B., & Kumar, P. (2006). A survey of simulated annealing as a tool for single and multiobjective optimization. Journal of the operational research society, 57(10), 1143-1160.
- Vincent, F. Y., & Lin, S. W. (2014). Multi-start simulated annealing heuristic for the location routing problem with simultaneous pickup and delivery. Applied soft computing, 24, 284-290.
- Ahonen, H., de Alvarenga, A. G., & Amaral, A. R. S. (2014). Simulated annealing and tabu search approaches for the corridor allocation problem. European Journal of Operational Research, 232(1), 221-233.
- Vincent, F. Y., Jewpanya, P., Redi, A. P., & Tsao, Y. C. (2021). Adaptive neighborhood simulated annealing for the heterogeneous fleet vehicle routing problem with multiple cross-docks. Computers & operations research, 129, 105205.
- Yu, V. F., Jewpanya, P., & Perwira Redi, A. A. N. (2014). A simulated annealing heuristic for the vehicle routing problem with cross-docking. Logistics Operations, Supply Chain Management and Sustainability, 575-584.
parida 