In this paper, we review parallel search techniques for approximating the global optimal solution of combinatorial optimization problems. Recent developments on parallel implementation of genetic algorithms, simulated annealing, tabu search, and greedy randomized adaptive search procedures (GRASP) are discussed.

Simulated annealing based standard cell placement for VLSI designs has long been acknowledged as a compute-intensive process. All previous work in parallel simulated annealing based placement has minimized area, but with deep submicron design, minimizing wirelength delay is also needed. The algorithm discussed in this paper is the first parallel algorithm for timing driven placement. We have us...

Simulated annealing algorithms for VLSI layout tasks produce solutions of high quality but are computationally expensive. This thesis examines some parallel approaches to accelerate simulated annealing using message-passing multiprocessors with a hypercube architecture. Floorplanning is chosen as a typical application of annealing in physical design. Different partitioning strategies which map ...

Simulated annealing has proven to be a good technique for solving hard combina-torial optimization problems. Some attempts at speeding up annealing algorithms have been based on shared memory multiprocessor systems. Also parallelizations for certain problems on distributed memory multiprocessor systems are known. In this paper, we present a problem independent general purpose parallel implement...

Simulated annealing has proven to be a good technique for solving hard combinatorial optimization problems. Some attempts at speeding up annealing algorithms have been based on shared memory multiprocessor systems. Also parallelizations for certain problems on distributed memory multiprocessor systems are known. In this paper, we present a problem independent general purpose parallel implementa...

A study of simulated annealing and a revised cascade algorithm for image reconstruction. Simple parallel hierarchical and relaxation algorithms for segmenting noncausal Markovian random elds.

The traveling salesman problem (TSP) is to find a tour of a given number of cities (visiting each city exactly once and returning to the starting city) where the length of this tour is minimized. In this project, we implemented solutions to the traveling salesman problem using parallel genetic algorithm and simulated annealing, and compared the parallel performance and results of these two impl...

In this study, a temperature parallel simulated annealing with adaptive neighborhood (TPSA/AN) for continuous optimization problems is introduced. TPSA/AN is based on the temperature parallel simulated annealing (TPSA), which is suitable for parallel processing, and the SA that Corana developed for continuous optimization problems. The moves in TPSA/AN are adjusted to have equal acceptance rate...