Deterministic annealing

Key words Library design, combinatorial optimization, deterministic annealing. 

Rose, K. (1998) Deterministic annealing for clustering, compression, classification, regression and related optimization problems. Proc IEEE 86(11), 2210-2239. 

Other methods which are applied to conformational analysis and to generating multiple conformations and which can be regarded as random or stochastic techniques, since they explore the conformational space in a non-deterministic fashion, arc genetic algorithms (GA) [137, 1381 simulation methods, such as molecular dynamics (MD) and Monte Carlo (MC) simulations 1139], as well as simulated annealing [140], All of those approaches and their application to generate ensembles of conformations arc discussed in Chapter II, Section 7.2 in the Handbook. 

II with a new chapter (for the second edition) on global optimization methods, such as tabu search, simulated annealing, and genetic algorithms. Only deterministic optimization problems are treated throughout the book because lack of space precludes discussing stochastic variables, constraints, and coefficients. 

D. Shalloway, Packet Annealing A Deterministic Method for Global Minimization. Application to Molecular Conformation, in Recent Advances in Global Optimization, C. A. Floudas and P. M. Pardalos, eds., Princeton Series in Computer Science, Princeton Univ. Press, Princeton, NJ, 1996, pp. 433-477. 

Performance of two different algorithms namely simulated annealing and tabu search for solving MDVRP with inventory transfer between depots in a three-echelon supply chain was studied by Fard and Setak (2011). Three-echelon supply chain composed of a single plant, multiple distribution centers and a set of retailers with deterministic demands. The results depicted that the tabu search approach outperformed the simulated annealing approach in terms of quality of solution. 

---