Assignment problems in parallel and distributed computing
Assignment problems in parallel and distributed computing
Models of machines and computation for mapping in multicomputers
ACM Computing Surveys (CSUR)
A Generalized Scheme for Mapping Parallel Algorithms
IEEE Transactions on Parallel and Distributed Systems
An adaptive scheme for predicting the usage of grid resources
Computers and Electrical Engineering
A hybrid particle swarm optimization for job shop scheduling problem
Computers and Industrial Engineering
A discrete version of particle swarm optimization for flowshop scheduling problems
Computers and Operations Research
Particle swarm optimization for integer programming
CEC '02 Proceedings of the Evolutionary Computation on 2002. CEC '02. Proceedings of the 2002 Congress - Volume 02
Computers and Operations Research
An efficient flow-shop scheduling algorithm based on a hybrid particle swarm optimization model
Expert Systems with Applications: An International Journal
A discrete particle swarm optimization algorithm for scheduling parallel machines
Computers and Industrial Engineering
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The grid scheduling problem is concerted with some tasks assigning to a grid distributed system that the relative tasks have to exchange information on different grids. In the original particle swarm optimization (PSO) algorithm, particles search solutions in a continuous solution space. Since the solution space of the grid scheduling problem is discrete. This paper presents a discrete particle swarm optimization (PSO) that combines the simulated annealing (SA) method to solve the grid scheduling problems. The proposed discrete PSO uses a population of particles through a discrete space on the basis of information about each particle's local best solution and global best solution of all particles. For generating the next solution of each particle, the SA is adopted into the discrete PSO. The objective is to minimize the maximum cost of the grid, which includes computing cost and communication cost. Simulation results show that the grid scheduling problem can be solved efficiently by the proposed method.