Add to ORKGAbstract. This paper considers parallel execution of the standard simulated an-nealing algorithm using speculative computing. Various heuristics for estimating the probabilities of move acceptance are advanced and their performance compared experimentally. Some are found to be superior to methods previously published
This paper reports the results of experiments carried out to test the value of randomness in the acc...
Speculative evaluation, including leniency and futures, is often used to produce high degrees of par...
Abstract- A compile-time analysis technique is developed to derive the probability with which a user...
Simulated annealing is known to be an efficient method for combinatorial optimization problems. Its ...
Temperature is the control parameter of Simulated Annealing, one of the best-known local search opti...
This paper focuses on the problem of how to find and effectively exploit speculative thread-level pa...
An overview of physical annealing and simulated annealing methods is presented. The target audience ...
This paper focuses on the problem of how to find and effectively exploit speculative thread-level pa...
Simulated annealing is a combinatorial optimization method based on randomization techniques. The me...
Many problems in Artificial Intelligence involve traversing large search-spaces. Such problems typic...
This book presents state of the art contributes to Simulated Annealing (SA) that is a well-known pro...
Evolutionary algorithms are often used for hard optimization problems. Solving time of this problems...
Since its introduction as a generic heuristic for discrete optimisation in 1983, simulated annealing...
This paper introduces and analyzes a parallel method of simulated annealing. Borrowing from genetic ...
Simulated annealing is a combinatorial optimization method based on randomization techniques. The me...
This paper reports the results of experiments carried out to test the value of randomness in the acc...
Speculative evaluation, including leniency and futures, is often used to produce high degrees of par...
Abstract- A compile-time analysis technique is developed to derive the probability with which a user...
Simulated annealing is known to be an efficient method for combinatorial optimization problems. Its ...
Temperature is the control parameter of Simulated Annealing, one of the best-known local search opti...
This paper focuses on the problem of how to find and effectively exploit speculative thread-level pa...
An overview of physical annealing and simulated annealing methods is presented. The target audience ...
This paper focuses on the problem of how to find and effectively exploit speculative thread-level pa...
Simulated annealing is a combinatorial optimization method based on randomization techniques. The me...
Many problems in Artificial Intelligence involve traversing large search-spaces. Such problems typic...
This book presents state of the art contributes to Simulated Annealing (SA) that is a well-known pro...
Evolutionary algorithms are often used for hard optimization problems. Solving time of this problems...
Since its introduction as a generic heuristic for discrete optimisation in 1983, simulated annealing...
This paper introduces and analyzes a parallel method of simulated annealing. Borrowing from genetic ...
Simulated annealing is a combinatorial optimization method based on randomization techniques. The me...
This paper reports the results of experiments carried out to test the value of randomness in the acc...
Speculative evaluation, including leniency and futures, is often used to produce high degrees of par...
Abstract- A compile-time analysis technique is developed to derive the probability with which a user...