A genetic algorithm for assembling optical computers using faulty optical arrays

A digital optical computer architecture consists of several stages, or slots, of optical arrays. Each slot can be viewed as a rectangular array of locations which are classified as vital and extraneous, depending on whether or not the location is on an optical signal path. A defective optical array can be used in a slot provided that the defective locations of the array do not coincide with the vital locations of the slot. The problem of low manufacturing yield of optical arrays can be alleviated by utilizing defective arrays that are consistent with slots. The mapping of arrays to slots so as to maximize the number of machines that can be assembled is a difficult discrete optimization problem. This is because a larger array can become consistent to a slot through transformations such as translation and rotation. We propose the use of evolutionary programming for the assembly of optical computers. Our experimental results indicate that a genetic algorithm is a powerful technique to search the vast solution space efficiently