Hi, in fact PSO algorithm have more sense whan trying to minimize a real function. In case of integar variables you should perhaps better try other adapted algorithms.

Thanks Richard, I have a develop this algorithm in the class of Master. But the refences in this case dont exist.

Hi, another possibility would be to adapt random search methods to the integar case simply by adding a round() instruction to choose the nearest integer of a given real value.

Hi, I agree with Professor Richard Epenoy, just you need to add the function round () in order to transform the real value into the nearest integer by truncation.

How are you initializing your velocity vectors and position vectors? I think, if you had initialized these vectors correctly (with same dimension), you could have avoided the error. 

We discovered rounding, etc, was not the best approach for PSOs and discrete sets of integers. There is an adapted PSO addressing this for discretes. We were able to combine this with the other types of PSOs. There is a "Discrete Particle Swarm Optimization" algorithm. Below is a reference that might help.

http://www.sciencedirect.com/science/article/pii/S1568494613003013

Consider using Yannis Marinakis discrete PSO.  I recommend the paper "Particle Swarm Optimization for the Vehicle Routing Problem with Stochastic Demands" http://www.sciencedirect.com/science/article/pii/S1568494613000240

The PSO algorithm is now available in general for the real case but you can adapt it easily by adding a simple instruction. 

Hi, we can adapt the random search to this particular case simply. I applied this algorithm to many cases and it works very well.