Category decomposition method for un-mixing of mixels (Mixed Pixels) which is acquired with spaceborne based visible to near infrared radiometers by means of Maximum Entropy Method (MEM) with parameter estimation based on Simulated Annealing: SA is proposed. Through simulation studies with spectral characteristics of the ground cover targets which are derived from spectral library and actual re...

In this paper color image segmentation is accomplished using MRF model. The problem is formulated as a pixel labeling and the true labels are modeled as the MRF model. The observed color image is assumed to be the degraded version of the true labels. We assume the degradation to be Gaussian distribution. The label estimates are obtained by using Bayesian framework and MAP criterion. The (I1, I2...

Method for noise suppressing edge enhancement based on genetic algorithm taking into account complexity of target images measured with fractal dimension is proposed. Through experiments with satellite remote sensing imagery data with additive noise, it is found that the proposed method shows appropriate edge enhancing performance with suppressing the additive noise in accordance with complexity...

This paper proposes Parallel Simulated Annealing using Genetic Crossover (PSA/GAc). In this algorithm, there are several processes of Simulated Annealing (SA) working parallel. To exchange information between the solutions, the operation of genetic crossover is performed. Through the continuous test problems, it is found that PSA/GAc can search the solution effectively. The proposed algorithm i...

Because of its highly combinatorial aspect, its dynamic nature and its practical interest for manufacturing systems, the scheduling problem has been widely studied in the literature by various methods: heuristics, constraint propagation techniques, Constraint Satisfaction Problem formalism, simulated annealing, Taboo search, genetic algorithms, neural networks, etc. This paper deals with the Fl...

The quadratic assignment problem (QAP) is one of the most difficult combinatorial optimization problems. An effective heuristic for obtaining approximate solutions to the QAP is simulated annealing (SA). Here we describe an SA implementation for the QAP which runs on a graphics processing unit (GPU). GPUs are composed of low cost commodity graphics chips which in combination provide a powerful ...

This paper proposes a new algorithm using Simulated Annealing (SA) for stochastic scheduling. Stochastic effects are added with nondeterministic activity durations. Simple simulated annealing can not properly handle such a complex problem so an improved version is produced and utilized within the algorithm. Generally, the availability of resources is not enough to complete all the current activ...

Quadratic Assignment Problem (QAP) is an NPhard combinatorial optimization problem, therefore, solving the QAP requires applying one or more of the meta-heuristic algorithms. This paper presents a comparative study between Meta-heuristic algorithms: Genetic Algorithm, Tabu Search, and Simulated annealing for solving a real-life (QAP) and analyze their performance in terms of both runtime effici...

This paper explores the use of simulated annealing (SA) for solving arbitrary combinatorial optimisation problems. It reviews an existing code called GPSIMAN for solving 0-1 problems, and evaluates it against a commercial branch-and-bound code, OSL. The problems tested include travelling salesman, graph colouring, bin packing, quadratic assignment and generalised assignment. The paper then desc...