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MMGAs> Clearing: Restricted Competition Selection (RCS)

                                                                                                                                                                                                                                                                

 

Last update: 06/2011

 

 

     Parameters

 

 

Niche radius (σshare)

Size of Elite Set (M)

 

 

     Description

 

This method uses the principles of the clearing  in the stage of substitution instead of in the selection. Moreover, all the individuals of the initial population are obligated to enter in the matting pool, randomly grouping them in pairs for the reproduction process. This removes the pressure on the selection.

 

It starts randomly putting into pairs the individuals of the original population of each generation for the process of reproduction, not counting on selection. However, it introduces pressure on substitution where in order to limit the competition among individuals from different niches it establishes a system based on the clearing by which only the best of each niche may survive.

 

For this, it uses two groups: the elite and the competition sets. The former (Elite Set) is obtained from the original population and with the objective of maintaining the good solutions found during the searching process following the principles of classical elitism. To obtain them, the population is put into order and the M best individuals among the k best of each niche are searched, and these are reserved for the substitution process.

 

The second one (Competition Set) is formed by joining together the Elite Set to the population of the new individuals created starting from reproduction (Children Population). Out of this group, the N individuals that will form the population of the following generation are obtained. For this, it is searched among the M+N individuals sorted out from higher to lower quality the best Ns from the best of each niche

 

This process is shown in the following flowchart:

 

 

 

     Executable

 

The following three files have to be in the same folder. Do not change the name of the file. Double-click the .exe file to run it.

 

  JSSP

Executable

exe

Data File

Open .txt file of the instance you want to run (for JSSP), copy and paste its contents inside this file.

D_Entrada

Parameters File

Open the file and change the parameters

D_Algoritmo

 

The following five files of solutions are generated:

D_Sal_Mejores-txt (includes the best solutions).

D_Sal_Optimos (includes the value of the objective function, i.e., Cmax).

D_Sal_NumOptimos (includes the number of different solutions where the optima value specified in the data file has been reached). This file is empty if this value is not reached.

D_Sal_Distancias (includes the distances between solutions where the optima value specified in the data file has been reached). This file is empty if either this value is not reached or only one solution is achieved.

D_Sal_Soluciones (includes the schedule of the solutions where the optima value specified in the data file has been reached). This file is empty if this value is not reached.

 

 

     References

 

Lee, Ch, Cho, D and Jung, H. (1999). Niching genetic algorithm with restricted competition selection for multimodal function optimization. IEEE transactions on magnetics (35) 1722-1725

 
   

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