We present a new deterministic algorithm for simulated annealing and demonstrate its applicability with several classical examples: the ground state energies of the 2d and 3d short range king spin glasses, the traveling salesman problem, and pattern recognition in computer vision. Our algorithm is based on a microcanonical Monte Carlo method and is shown to be a powerful tool for the analysis o...

In this paper, we examine the different measures of Fault Tolerance in a Distributed Simulated Annealing process. Optimization by Simulated Annealing on a distributed system is prone to various sources of failure. We analyse simulated annealing algorithm, its architecture in distributed platform and potential sources of failures. We examine the behaviour of tolerant distributed system for optim...

In this communication Simulated Annealing and Genetic Algorithms, are applied to the graph partitioning problem. These techniques mimic processes in statistical mechanics and biology, respectively, and are the most popular meta-heuristics or general-purpose optimization strategies. A hybrid algorithm for circuit partitioning, which uses tabu search to improve the simulated annealing meta-heuris...

The purpose of this study is to develop one solution to the speech inverse filtering problem. A new efficient articulatory speech analysis scheme, identifying the articulatory parameters from the acoustic speech waveforms, was induced. The algorithm is known as simulated annealing, which is constrained to avoid non-unique solutions and local minima problems. The constraints are determined by th...

Simulated annealing is a probabilistic algorithm that has shown some promise when applied to combinatorially NP-hard problems. One advantage of the simulated annealing algorithm is that it is based on an analogy with statistical mechanics which is not problem-specific. However, any implementation of the algorithm for a given problem requires that several specific choices be made. The success or...

This paper presents a didactic Simulated Annealing placement tool. Simulated Annealing is a very famous generic combinatorial optimization algorithm that has been successfully applied to VLSI placement. Our tool allows any user to change several parameters of the algorithm and see their implications in the results graphically. At every algorithm step, the current placement disposition is displa...

Nowadays, there are many optimization problems where exact methods do not exist or where deterministic methods are computationally too complex to implement. Simulated annealing may be the answer for these cases. It is not greedy in the sense that it is not fool with false minima, and is pretty easy to implement. Furthermore, because it does not require a mathematical model, it can be used to so...

nowadays organization especially r&d; centers are dealing with project portfolio selection decisions under uncertainty. moreover in the most of the past research, project portfolio selection and scheduling are often considered to be independent problem. this leads to insufficient result in real world. so in this research simultaneous project portfolio selection and scheduling problem is modelin...

This paper investigates a global search optimisation technique, referred to as the repeated weighted boosting search. The proposed optimisation algorithm is extremely simple and easy to implement. Heuristic explanation is given for the global search capability of this technique. Comparison is made with the two better known and widely used global search techniques, known as the genetic algorithm...