Simulated annealing is a popular local search meta-heuristic used to address discrete and, to a lesser extent, continuous optimization problems. The key feature of simulated annealing is that it provides a means to escape local optima by allowing hill-climbing moves (i.e., moves which worsen the objective function value) in hopes of finding a global optimum. A brief history of simulated anneali...

Quantum annealing Quantum annealing (also known as alloy, crystallization or tempering) is analogous to simulated annealing but in substitution of thermal activation by quantum tunneling. The class of algorithmic methods for quantum annealing (dubbed: 'QA'), sometimes referred by the italian school as Quantum Stochastic Optimization ('QSO'), is a promising metaheuristic tool for solving local s...

Simulated Annealing has become a standard optimization technique for a wide variety of problems: starting at a random configuration and performing a sequence of moves, the system is optimized using a control parameter which partially allows for accepting a deterioration and therefore for climbing over barriers in the energy landscape. Our approach, Weight Annealing, changes the energy landscape...

Simulated annealing’s high computational intensity has stimulated researchers to experiment with various parallel and distributed simulated annealing algorithms for shared memory, message-passing, and hybrid-parallel platforms. MapReduce is an emerging distributed computing framework for large-scale data processing on clusters of commodity servers; to our knowledge, MapReduce has not been used ...

In this paper, a positive effect of rapid thermal annealing (RTA) technique has been researched and compared with conventional furnace annealing for Si nanocrystalline in silicon carbide (SiC) matrix system. Amorphous Si-rich SiC layer has been deposited by co-sputtering in different Si concentrations (50 to approximately 80 v%). Si nanocrystals (Si-NC) containing different grain sizes have bee...

A simulated annealing method is described for training hidden Markov models and producing multiple sequence alignments from initially unaligned protein or DNA sequences. Simulated annealing in turn uses a dynamic programming algorithm for correctly sampling suboptimal multiple alignments according to their probability and a Boltzmann temperature factor. The quality of simulated annealing alignm...

Quantum annealing is a general strategy for solving difficult optimization problems with the aid of quantum adiabatic evolution. Both analytical and numerical evidence suggests that under idealized, closed system conditions, quantum annealing can outperform classical thermalization-based algorithms such as simulated annealing. Current engineered quantum annealing devices have a decoherence time...

The effect of the initial microstructure and intercritical annealing on mechanical properties and work-hardening response of a high-formability low carbon steel were studied. The work-hardening analysis was based on the modified Crussard–Jaoul method. The ferritic-pearlitic sheets showed low strength and high total elongation with the appearance of the yield point phenomenon. The occurrence of ...