Amended Fruit fly Optimization

Amended Fruit fly Optimization

According to food finding characteristics of fruit fly swarm, the whole procedure of the original FOAcan be divided into several step as follows:-

ALGORITHM FOR aFOA

Step 1 Start:

            Start the algorithm.

Step 2 Parameter Initialization:        

            The main parameters of aFOA are maximum iteration number, the population size.

Step 3 Population Initialization:

            Randomly initialize the population size is NP. Randomly produce solution, half blending and un-blending.

Step 4 Neighborhood Generations and Find Best

           Neighborhood:

            NN neighborhoods are randomly generated. NN neighborhoods are produced by three kinds of neighborhood search. Find out the best neighbor.

Step 5 Replacements of Neighbor:

            If the best neighbor is better than the fly then replace the fly with the best neighbor and go to next step, else go to next step without replacing.

Step 6 Local Neighborhood Loop Search:

            If the loop termination is reached then sort the population else go back to step 4.

Step 7 Crossovers:

            In global cooperation search each flies in the poor half crossover it with the corresponding one. If new fly is better than poor fly then replace the poor fly with new one and go to next step, else go to next step without replacing.

Step 8 Termination Criterion:

             If termination standard is reached then provide result, else go back to step 3.

Step 9 End:

            End the algorithm.

 

Anurag Rana