Genetic programming: on the programming of computers by means of natural selection
Genetic programming: on the programming of computers by means of natural selection
Genetic programming II: automatic discovery of reusable programs
Genetic programming II: automatic discovery of reusable programs
A compiling genetic programming system that directly manipulates the machine code
Advances in genetic programming
Genetic programming: an introduction: on the automatic evolution of computer programs and its applications
Sub-machine-code genetic programming
Advances in genetic programming
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Programming III: Darwinian Invention & Problem Solving
Genetic Programming III: Darwinian Invention & Problem Solving
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Genetic Programming and Evolvable Machines
Uniform Crossover in Genetic Algorithms
Proceedings of the 3rd International Conference on Genetic Algorithms
Proceedings of the European Conference on Genetic Programming
Dynamic Programming
Guest Column: NP-complete problems and physical reality
ACM SIGACT News
Solving the Hamiltonian path problem with a light-based computer
Natural Computing: an international journal
Ultrafast Digital-Optical Arithmetic Using Wave-Optical Computing
OSC '08 Proceedings of the 1st international workshop on Optical SuperComputing
Solving NP-Complete Problems with Delayed Signals: An Overview of Current Research Directions
OSC '08 Proceedings of the 1st international workshop on Optical SuperComputing
Solving the subset-sum problem with a light-based device
Natural Computing: an international journal
The traveling beams optical solutions for bounded NP-complete problems
FUN'07 Proceedings of the 4th international conference on Fun with algorithms
A light-based device for solving the hamiltonian path problem
UC'06 Proceedings of the 5th international conference on Unconventional Computation
No free lunch theorems for optimization
IEEE Transactions on Evolutionary Computation
A comparison of linear genetic programming and neural networks inmedical data mining
IEEE Transactions on Evolutionary Computation
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Designing optical devices for solving NP-complete problems is a difficult task. The difficulty consists in constructing a graph which - when traversed by light - generates all possible solutions of the problem to be solved. So far only few devices of this type have been proposed. Here we suggest the use of evolutionary algorithms for solving this problem: the graphs are generated using a special Genetic Programming approach. We have tested our idea on the subset sum problem. Numerical experiments shows the effectiveness of the proposed approach.