Each gene in the chromosome is of different type. Is it possible to apply genetic operators(selection, crossover, mutation) on such a varying gene structure chromosome. Is there any suitable evolutionary algorithm for varying structured gene?
Probably you will not find an out of the box implemented EA for this situation, but it is possible to implement one. Lets say you have part integer, part real and part binary genes. An idea is to implement a kind of crossover for each part (real crossover, integer crossover and a binary crossover) that works on that part (like use half of a given part from each parent) and a complete crossover that random takes one to tree parts and do the crossover. Do the same for the mutation and I think it will work.
You may find other ideas doing a search into some articles:
Maiti, A. K., A. K. Bhunia, and Manoranjan Maiti. "An application of real-coded genetic algorithm (RCGA) for mixed integer non-linear programming in two-storage multi-item inventory model with discount policy." Applied Mathematics and computation 183.2 (2006): 903-915.
"Abstract
The purpose of this research work is to solve mixed-integer non-linear programming problem with constraints by a real-coded genetic algorithm (RCGA). (...)"
Deep, Kusum, et al. "A real coded genetic algorithm for solving integer and mixed integer optimization problems." Applied Mathematics and Computation 212.2 (2009): 505-518.
"Abstract
In this paper, a real coded genetic algorithm named MI-LXPM is proposed for solving integer and mixed integer constrained optimization problems. (...)"
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