Optimization through simulation is considered an efficient tool in dealing with optimization problems. It’s a tool that is capable to cover real world problems to a much more complete way than the other optimization tools. The problem of this tool is the necessity of heavy processing computations. This problem is caused not only since the simulation process is time consuming, but the objective function value at a point of the solution space is required to simulate multiple performances. Meta-models are approaches to deal with this dilemma and have other problems that limit their use. Meta-model remodel the simulation model; it reduces the complexity of the model and yet the model still further away from the real world In this paper, the particle swarm optimization is modified so that can addition to remove the meta-models, reduce time to achieve optimal response.
Azadeh, A., Pashapour, S., & Shiri, H. (2014). Implementation of Particle Swarm Algorithm in Optimization Approach Using Simulation. Advances in Industrial Engineering, 48(1), 1-11. doi: 10.22059/jieng.2014.51145
MLA
A. Azadeh; Sh. Pashapour; H. Shiri. "Implementation of Particle Swarm Algorithm in Optimization Approach Using Simulation", Advances in Industrial Engineering, 48, 1, 2014, 1-11. doi: 10.22059/jieng.2014.51145
HARVARD
Azadeh, A., Pashapour, S., Shiri, H. (2014). 'Implementation of Particle Swarm Algorithm in Optimization Approach Using Simulation', Advances in Industrial Engineering, 48(1), pp. 1-11. doi: 10.22059/jieng.2014.51145
VANCOUVER
Azadeh, A., Pashapour, S., Shiri, H. Implementation of Particle Swarm Algorithm in Optimization Approach Using Simulation. Advances in Industrial Engineering, 2014; 48(1): 1-11. doi: 10.22059/jieng.2014.51145
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