An algorithm using the heuristic technique of Simulated Annealing to solve a scheduling problem is presented, focusing on the scheduling issues. The approximated method is examined together with its ...

Computational grids have become attractive and promising platforms for solving large-scale high-performance applications of multi-institutional interest. However, the management of resources and ...

Scheduling is a very important part of the cloud computing system. This paper introduces an optimized algorithm for task scheduling based on genetic simulated annealing algorithm in cloud computing ...

Simulated annealing is a heuristic algorithm that mimics the process of cooling a metal to find its lowest energy state. It can be used to optimize complex systems that have many possible ...

This paper presents a simulated annealing algorithm to minimize makespan of single machine scheduling problem with uniform parallel machines. ... “Bounds for Multifit Scheduling on Uniform Processors, ...

Hybrid genetic algorithm-simulated annealing (HGASA) algorithm is the combination of genetic algorithm (GA) with simulated annealing as a local search method to accelerate the convergence speed. The ...

This project explores various algorithms for solving the Graph Partitioning Problem, aiming to divide the vertices of a graph into a specified number of subsets while minimizing the number of edges ...

D-Wave's quantum annealing processor, however, is only reflective of one particular branch of quantum computing: based on a system that is capable of optimizing itself to reach the lowest energy ...

The FCC simulated annealing took about a month to run on Sunsoft Fortran 95, Solaris 2.5.1 and a pizza box SPARC. For each partial solution. It is pretty amazing what simulated annealing can do.