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: an introduction: on the automatic evolution of computer programs and its applications
Logic Minimization Algorithms for VLSI Synthesis
Logic Minimization Algorithms for VLSI Synthesis
IEEE Intelligent Systems
Evolving parallel machine programs for a multi-ALU processor
CEC '02 Proceedings of the Evolutionary Computation on 2002. CEC '02. Proceedings of the 2002 Congress - Volume 02
On the futility of blind search: An algorithmic view of “no free lunch”
Evolutionary Computation
Parallel programs are more evolvable than sequential programs
EuroGP'03 Proceedings of the 6th European conference on Genetic programming
No free lunch theorems for optimization
IEEE Transactions on Evolutionary Computation
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Genetic Parallel Programming (GPP) is a novel Genetic Programming paradigm. Based on the GPP paradigm and a local search operator - FlowMap, a logic circuit synthesizing system integrating GPP and FlowMap, a Hybridized GPP based Logic Circuit Synthesizer (HGPPLCS) is developed. To show the effectiveness of the proposed HGPPLCS, six combinational logic circuit problems are used for evaluations. Each problem is run for 50 times. Experimental results show that both the lookup table counts and the propagation gate delays of the circuits collected are better than those obtained by conventional design or evolved by GPP alone. For example, in a 6-bit one counter experiment, we obtained combinational digital circuits with 8 four-input lookup tables in 2 gate level on average. It utilizes 2 lookup tables and 3 gate levels less than circuits evolved by GPP alone.