In this paper, we present a parallel simulated annealing (SA) on distributed computing resources. The parallel SA include two types of cooperation mechanism: inner group and inter group cooperations. In the inner group cooperation, SA processes start from the same initial point, however, move to different direction. That is, two concepts: concentration and diversity are included. On the other h...

In this paper, an unequal area Cyclic Facility Layout Problem (CFLP) is studied. Dynamic and seasonal nature of the product demands results in the necessity for considering the CFLP where product demands as well as the departmental area requirements are changing from one period to the next one. Since the CFLP is NP-hard, we propose a Simulated Annealing (SA) metaheuristic with a dynamic tempera...

The paper describes existing applications of probabilistic methods, namely simulated annealing and genetic algorithms, in solving problems concerning triangulated models. Most of applications are related to global optimization triangulation criteria, improvement of shapes of triangles or tetrahedra and positions of vertices, sometimes in the context of digital images. The paper also sums up typ...

The authors propose a new data dimensionality reduction method that is formulated as an optimization problem solved in two stages. In the first stage, Generalized Principal Component Analysis (GPCA) is used to find a solution with local maximum (local solution) whereas the algorithm Simulated Annealing (SA) is performed, in the second stage, to converge the local solution to the optimal solutio...

Flexible job shop scheduling problem (FJSP) is one of the hardest combinatorial optimization problems known to be NP-hard. This paper proposes a novel hybrid imperialist competitive algorithm with simulated annealing (HICASA) for solving the FJSP. HICASA explores the search space by using imperial competitive algorithm (ICA) and use a simulated annealing (SA) algorithm for exploitation in the s...

We have developed a hybrid optimization algorithm for inversion of gravity data using a binary formulation. The new algorithm utilizes the Genetic Algorithm (GA) as a global search tool, while implementing Quenched Simulated Annealing (QSA) intermittently for local search. The hybrid has significantly decreased computational cost over GA or Simulated Annealing (SA) alone and has allowed for suc...

In this paper, a solution to the multichannel image restoration problem is provided using compound Gauss Markov random elds. For the single channel deblurring problem the convergence of the Simulated Annealing (SA) and Iterative Conditional Mode (ICM) algorithms has not been established. We propose two new iterative multichannel restoration algorithms which can be considered as extensions of th...

This paper proposes a hybrid optimization method based on the fusion of the Simulated Annealing (SA) and Clonal Selection Algorithm (CSA), in which the SA is embedded in the CSA to enhance its search capability. The novel optimization algorithm is also employed to deal with several nonlinear benchmark functions as well as a practical engineering design problem. Simulation results demonstrate th...

In this paper a hybrid technique of Genetic Algorithm and Simulated Annealing (HGASA) is applied for Fractal Image Compression (FIC). With the help of this hybrid evolutionary algorithm effort is made to reduce the search complexity of matching between range block and domain block. The concept of Simulated Annealing (SA) is incorporated into Genetic Algorithm (GA) in order to avoid pre-mature c...

GA genetic algorithm HGA hybrid genetic algorithm SA simulated annealing algorithm ACO ant colony optimization TS tabu search IA immune algorithm GDA great deluge algorithm CEA cellular evolutionary approach NN neural network NFT near feasible threshold UGF universal generating function MSS multi-state system RB/i/j recovery block architecture that can tolerate i hardware and j software faults ...