[[abstract]]A scalable linear algorithm of simulated annealing (SA) was proposed by Lin et al. that is capable of achieving a near optimal solution for the travelling saleman problem in a controllable way. Since the linearity is based on the hybrid mechanism that combines SA heuristics with the scaling relation of acceptance ratio in the low temperature, other conventional heuristics in optimisation problems ought to be tried. The nearest-neighbour (NN) heuristics is thus studied, and one finds that the quenched configuration of NN's could be resurrected back to SA path by the hybrid mechanism. It is also verified that the same scalable linear algorithm of Lin's may continue to apply with exactly the same set of parameters.[[notice]]補正完
This paper is concerned with a novel optimization algorithm that implements an enhanced formulation ...
Abstract. Global optimization involves the difficult task of the identification of global extremitie...
Simulated annealing is a probabilistic optimization algorithm which is used for approximating the gl...
[[abstract]]Complex optimisation problems with many degrees of freedom are often characterised by th...
International audienceFinding the global minimum of a nonconvex optimization problem is a notoriousl...
Complex nonlinear optimization problems require specific resolution techniques. These problems are o...
Simulated annealing is a general approach for approximately solving large combinatorial optimization...
The Metropolis algorithm is simulated annealing with a fixed temperature. Surprisingly enough, many ...
The goal of the research out of which this monograph grew, was to make annealing as much as possible...
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...
Simulated annealing and related Monte Carlo-type optimization algorithms are used to apply statistic...
The Random House Dictionary defines anneal as ... to free (glass, metals, etc.) from internal stre...
This book presents state of the art contributes to Simulated Annealing (SA) that is a well-known pro...
In this paper, a new Modified Meta-Heuristic algorithm is proposed. This method contains some modifi...
This paper is concerned with a novel optimization algorithm that implements an enhanced formulation ...
Abstract. Global optimization involves the difficult task of the identification of global extremitie...
Simulated annealing is a probabilistic optimization algorithm which is used for approximating the gl...
[[abstract]]Complex optimisation problems with many degrees of freedom are often characterised by th...
International audienceFinding the global minimum of a nonconvex optimization problem is a notoriousl...
Complex nonlinear optimization problems require specific resolution techniques. These problems are o...
Simulated annealing is a general approach for approximately solving large combinatorial optimization...
The Metropolis algorithm is simulated annealing with a fixed temperature. Surprisingly enough, many ...
The goal of the research out of which this monograph grew, was to make annealing as much as possible...
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...
Simulated annealing and related Monte Carlo-type optimization algorithms are used to apply statistic...
The Random House Dictionary defines anneal as ... to free (glass, metals, etc.) from internal stre...
This book presents state of the art contributes to Simulated Annealing (SA) that is a well-known pro...
In this paper, a new Modified Meta-Heuristic algorithm is proposed. This method contains some modifi...
This paper is concerned with a novel optimization algorithm that implements an enhanced formulation ...
Abstract. Global optimization involves the difficult task of the identification of global extremitie...
Simulated annealing is a probabilistic optimization algorithm which is used for approximating the gl...