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Abstract

Software development for schematic design in an automated digital circuit

production process

Artificial intelligence has transformed industrial activities. One of the important

applications of artificial intelligence is the reduction of computing optimization costs.

In recent years, we have noticed the increasing use of artificial intelligence to solve

problems with great time complexity.

By optimization we mean that we minimize or maximize some sizes depending on the

problem we have to deal with.

Optimization algorithms are classified into two types: precise algorithms and

approximate algorithms. Precise algorithms can accurately find optimal solutions, but they do

not apply to complex optimization problems and their solution time increases exponentially in

such problems. Approximate algorithms can find almost optimal solutions to difficult

optimization problems in a short period of time.

In the present dissertation, we solve approximately a problem of optimization under

constraints using genetic algorithm. More specifically, we solve the problem of creating

optimized schematic digital circuits. There are two main sub-problems we have to deal with,

firstly the problem of placing objects in two-dimensional space in an optimal way and

secondly the problem of finding the shortest path to interconnect the components with each

other.

In addition, we will use the Logisim tool which is software for designing digital

circuits. Logisim is open source software, used by University departments to conduct Digital

Design courses and is available for free use. You can download it for free from

For this reason, a command-line tool was developed, which accepts a file (.dot) as the

input with the definition of the digital circuit, and as an output, we get a file (.circ) compatible

with Logisim, which contains the schematic of the digital circuit after optimization.

Schematic optimization can be greatly influenced by the user through the command line

arguments.