Advanced fitness landscape analysis and the performance of memetic algorithms
Evolutionary Computation - Special issue on magnetic algorithms
Phase transition in a random NK landscape model
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
Phase transition in a random NK landscape model
Artificial Intelligence
Analysis of estimation of distribution algorithms and genetic algorithms on NK landscapes
Proceedings of the 10th annual conference on Genetic and evolutionary computation
PRICAI '08 Proceedings of the 10th Pacific Rim International Conference on Artificial Intelligence: Trends in Artificial Intelligence
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
An analysis of phase transition in NK landscapes
Journal of Artificial Intelligence Research
Lower and upper bounds for linkage discovery
IEEE Transactions on Evolutionary Computation
Energy landscape for Hopfield network programmed with program clauses
ACST '08 Proceedings of the Fourth IASTED International Conference on Advances in Computer Science and Technology
NK landscapes, problem difficulty, and hybrid evolutionary algorithms
Proceedings of the 12th annual conference on Genetic and evolutionary computation
Network crossover performance on NK landscapes and deceptive problems
Proceedings of the 12th annual conference on Genetic and evolutionary computation
Intelligent Data Analysis - Artificial Intelligence
Performance of network crossover on NK landscapes and spin glasses
PPSN'10 Proceedings of the 11th international conference on Parallel problem solving from nature: Part II
Mutation rates of the (1+1)-EA on pseudo-boolean functions of bounded epistasis
Proceedings of the 13th annual conference on Genetic and evolutionary computation
Analysis of epistasis correlation on NK landscapes with nearest-neighbor interactions
Proceedings of the 13th annual conference on Genetic and evolutionary computation
Linkage tree genetic algorithms: variants and analysis
Proceedings of the 14th annual conference on Genetic and evolutionary computation
Adaptation of a multiagent evolutionary algorithm to NK landscapes
Proceedings of the 15th annual conference companion on Genetic and evolutionary computation
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N-K fitness landscapes have been used widely as examples and test functions in the field of evolutionary computation. We investigate the computational complexity of the problem of optimizing the N-K fitness functions and related fitness functions. We give an algorithm to optimize adjacent-model N-K fitness functions, which is polynomial in N. We show that the decision problem corresponding to optimizing random-model N-K fitness functions is NP-complete for K1, and is polynomial for K=1. If the restriction that the ith component function depends on the ith bit is removed, then the problem is NP-complete, even for K=1. We also give a polynomial-time approximation algorithm for the arbitrary-model N-K optimization problem.