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Seyedali Mirjalili

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14 Nov 2014 Screenshot Autonomous Groups Particles Swarm Optimization (AGPSO) A Particle Swarm Optimization Algorithm with Autonomous Groups of Particles Author: Seyedali Mirjalili particle swarm optimi..., pso, optimization, constrained optimizat..., heuristic, algorithm 49 0
31 Oct 2014 Screenshot Binary hybrid particle swarm optimization and gravitational search algorithm (BPSOGSA) Binary version of the BPSOGSA algorithm Author: Seyedali Mirjalili psogsa, pso, particle swarm optimi..., gravitational search ..., gsa, bpsogsa 48 0
31 Oct 2014 Screenshot Binary Bat Algorithm BBA is the binary version of the Bat Algorithm for optimizing binary problems. Author: Seyedali Mirjalili binary optimization, optimization, binary search space, ba, bba, swarm intelligence 58 1
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5.0 | 1 rating
31 Oct 2014 Screenshot Enhanced Binary Particle Swarm Optimization (BPSO) with 6 new transfer functions An Enhanced binary Particle Swarm Optimization algorithm (VPSO) with v-shaped transfer functions Author: Seyedali Mirjalili bpso, particle swarm optimi..., pso, transfer function, binary particle swarm..., discrete particle swa... 42 0
31 Oct 2014 Screenshot Adaptive gbest-guided gravitational search algorithm A gbest-guided gravitational search algorithm Author: Seyedali Mirjalili optimization, gsa, heuristic, evolutionary algorith..., ggsa, adaptive gbestguided ... 37 0
Comments and Ratings by Seyedali Mirjalili View all
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14 Nov 2014 Biogeography-Based Optimizer (BBO) for training Multi-Layer Perceptron (MLP) - Breast cancer dataset Biogeography-Based Optimizer (BBO) is employed as a trainer for Multi-Layer Perceptron (MLP) trainin Author: Seyedali Mirjalili

Hi Ko,

I did not underestand what you are trying to do exactly. Could you please clarify? If you change the dataset, you need to change the structure of the MLP as well (my_simulate.m file).

12 Nov 2014 Hybrid Particle Swarm Optimization and Gravitational Search Algorithm (PSOGSA) PSOGSA is the efficient combination of PSO and GSA. Author: Seyedali Mirjalili

Hi umair,

Just have a look at the benchmark_functions_details.m file.
You can define the dimension and variable for each dimension. The benchmark function 17 is a good example:

if Benchmark_Function_ID==17
down=[-5;0];up=[10;15];dim=2;
end

30 Aug 2014 Grey Wolf Optimizer (GWO) GWO is a novel meta-heuristic algorithm for global optimization Author: Seyedali Mirjalili

Hi Amr Hessan,

My thanks for identifying this issue. You are right. Every time alpha updates, we have to update beta and delta and well. I will consider this and update the files soon.

01 May 2014 Grey Wolf Optimizer (GWO) GWO is a novel meta-heuristic algorithm for global optimization Author: Seyedali Mirjalili

Hi Dalia,

This problem originates from your F5 function.

o=(100*(x(2:dim)-(x(1:dim-1).^2)).^2+(1-x(1:dim-1)).^2) returns a vector, while there should be a single fitness value for each search agent.
The formula for the F5 function has a sum in front of the expression as follows:
o=sum(100*(x(2:dim)-(x(1:dim-1).^2)).^2+(x(1:dim-1)-1).^2);

Generally speaking, each search agent should be assigned with only one fitness value.

Change your F5 function so that it returns a single value for each input vector, give it a try, and let me know.

Ali

08 Feb 2014 Improved Feedforward Neural Networks Using PSOGSA This program is an improved Feedforward Neural Network using a hybrid algorithm called PSOGSA. Author: Seyedali Mirjalili

Hi Sonmyadeep,

It depends on your dataset. You need to change FNNPSOGSA and My_FNN files according to your dataset. The codes are well-documented, so I believe if you spend time and understand the coeds it would be easy for you to modify it.

Comments and Ratings on Seyedali Mirjalili's Files View all
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01 Dec 2014 Grey Wolf Optimizer (GWO) GWO is a novel meta-heuristic algorithm for global optimization Author: Seyedali Mirjalili Hafiz

hi sir, can this GWO solve Economic Load Dispatch problem?

23 Nov 2014 Hybrid Particle Swarm Optimization and Gravitational Search Algorithm (PSOGSA) PSOGSA is the efficient combination of PSO and GSA. Author: Seyedali Mirjalili Ahmad Azar

14 Nov 2014 Biogeography-Based Optimizer (BBO) for training Multi-Layer Perceptron (MLP) - Breast cancer dataset Biogeography-Based Optimizer (BBO) is employed as a trainer for Multi-Layer Perceptron (MLP) trainin Author: Seyedali Mirjalili Seyedali Mirjalili

Hi Ko,

I did not underestand what you are trying to do exactly. Could you please clarify? If you change the dataset, you need to change the structure of the MLP as well (my_simulate.m file).

12 Nov 2014 Hybrid Particle Swarm Optimization and Gravitational Search Algorithm (PSOGSA) PSOGSA is the efficient combination of PSO and GSA. Author: Seyedali Mirjalili Seyedali Mirjalili

Hi umair,

Just have a look at the benchmark_functions_details.m file.
You can define the dimension and variable for each dimension. The benchmark function 17 is a good example:

if Benchmark_Function_ID==17
down=[-5;0];up=[10;15];dim=2;
end

12 Nov 2014 Hybrid Particle Swarm Optimization and Gravitational Search Algorithm (PSOGSA) PSOGSA is the efficient combination of PSO and GSA. Author: Seyedali Mirjalili umair

hi, please help me, i am using 3 variables with constraint limits. how i can set the upper and lower limit values of my variables

thanks in advance

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