Add to ORKGThis thesis is concerned with a novel algorithm, generalized from Chaotic Simulated Annealing (CSA) by adding a decreasing random noise into the neuron inputs in CSA to combine the best feature of both stochastic simulated annealing (SSA) and CSA, i.e., stochastic chaotic simulated annealing (SCSA).Master of Engineerin
Simulated annealing is a combinatorial optimization method based on randomization techniques. The me...
This paper explores the use of simulated annealing (SA) for solving arbitrary combinatorial optimisa...
Within the field of Computer Science, there exists a category called Optimization. Optimization can ...
This thesis is concerned with a novel algorithm, generalized from Chaotic Simulated Annealing (CSA) ...
In this thesis, a new general adaptive algorithm for solving a wide variety of NP-Complete combinato...
In this paper, we investigate the solving ability of Hop-field neural network with iterative simulat...
Simulated annealing is a combinatorial optimization method based on randomization techniques. The me...
Stochastic global optimization is a very important subject, that has applications in virtually all a...
We review the approaches for solving combinatorial optimization problems by chaotic dynamics. We men...
Swarm-based algorithm can successfully avoid the local optimal constraints, thus achieving a smooth ...
Simulated Annealing is a meta-heuristic that performs a randomized local search to reach near-optima...
In this paper, a new hybrid simulated annealing algorithm for constrained global optimizat...
Abstract. Two general-purpose metaheuristic algorithms for solving multiobjective stochastic combina...
International audienceFinding the global minimum of a nonconvex optimization problem is a notoriousl...
Based on the microcanonical Monte Carlo method of statistical physics, we present a new deterministi...
Simulated annealing is a combinatorial optimization method based on randomization techniques. The me...
This paper explores the use of simulated annealing (SA) for solving arbitrary combinatorial optimisa...
Within the field of Computer Science, there exists a category called Optimization. Optimization can ...
This thesis is concerned with a novel algorithm, generalized from Chaotic Simulated Annealing (CSA) ...
In this thesis, a new general adaptive algorithm for solving a wide variety of NP-Complete combinato...
In this paper, we investigate the solving ability of Hop-field neural network with iterative simulat...
Simulated annealing is a combinatorial optimization method based on randomization techniques. The me...
Stochastic global optimization is a very important subject, that has applications in virtually all a...
We review the approaches for solving combinatorial optimization problems by chaotic dynamics. We men...
Swarm-based algorithm can successfully avoid the local optimal constraints, thus achieving a smooth ...
Simulated Annealing is a meta-heuristic that performs a randomized local search to reach near-optima...
In this paper, a new hybrid simulated annealing algorithm for constrained global optimizat...
Abstract. Two general-purpose metaheuristic algorithms for solving multiobjective stochastic combina...
International audienceFinding the global minimum of a nonconvex optimization problem is a notoriousl...
Based on the microcanonical Monte Carlo method of statistical physics, we present a new deterministi...
Simulated annealing is a combinatorial optimization method based on randomization techniques. The me...
This paper explores the use of simulated annealing (SA) for solving arbitrary combinatorial optimisa...
Within the field of Computer Science, there exists a category called Optimization. Optimization can ...