On the complexity of protein folding (extended abstract)
STOC '98 Proceedings of the thirtieth annual ACM symposium on Theory of computing
Protein folding in the hydrophobic-hydrophilic (HP) is NP-complete
RECOMB '98 Proceedings of the second annual international conference on Computational molecular biology
A Fast Elitist Non-dominated Sorting Genetic Algorithm for Multi-objective Optimisation: NSGA-II
PPSN VI Proceedings of the 6th International Conference on Parallel Problem Solving from Nature
Reducing Local Optima in Single-Objective Problems by Multi-objectivization
EMO '01 Proceedings of the First International Conference on Evolutionary Multi-Criterion Optimization
Do additional objectives make a problem harder?
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Multiobjectivization by Decomposition of Scalar Cost Functions
Proceedings of the 10th international conference on Parallel Problem Solving from Nature: PPSN X
Investigations into the Effect of Multiobjectivization in Protein Structure Prediction
Proceedings of the 10th international conference on Parallel Problem Solving from Nature: PPSN X
Evolutionary algorithms and multi-objectivization for the travelling salesman problem
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
Optimal Triangulation in 3D Computer Vision Using a Multi-objective Evolutionary Algorithm
Proceedings of the 2007 EvoWorkshops 2007 on EvoCoMnet, EvoFIN, EvoIASP,EvoINTERACTION, EvoMUSART, EvoSTOC and EvoTransLog: Applications of Evolutionary Computing
Protein structure prediction in lattice models with particle swarm optimization
ANTS'10 Proceedings of the 7th international conference on Swarm intelligence
Twin Removal in Genetic Algorithms for Protein Structure Prediction Using Low-Resolution Model
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Helper-objective optimization strategies for the Job-Shop Scheduling Problem
Applied Soft Computing
Investigating relevant aspects of MOEAs for protein structures prediction
Proceedings of the 13th annual conference on Genetic and evolutionary computation
Parallel island-based multiobjectivised memetic algorithms for a 2D packing problem
Proceedings of the 13th annual conference on Genetic and evolutionary computation
Differential evolution for protein structure prediction using the HP model
IWINAC'11 Proceedings of the 4th international conference on Interplay between natural and artificial computation - Volume Part I
An Immune Algorithm for Protein Structure Prediction on Lattice Models
IEEE Transactions on Evolutionary Computation
Protein Folding in Simplified Models With Estimation of Distribution Algorithms
IEEE Transactions on Evolutionary Computation
Locality-based multiobjectivization for the HP model of protein structure prediction
Proceedings of the 14th annual conference on Genetic and evolutionary computation
Hybrid evolutionary algorithm with a composite fitness function for protein structure prediction
IDEAL'12 Proceedings of the 13th international conference on Intelligent Data Engineering and Automated Learning
An improved multiobjectivization strategy for HP model-based protein structure prediction
PPSN'12 Proceedings of the 12th international conference on Parallel Problem Solving from Nature - Volume Part II
Protein folding with cellular automata in the 3D HP model
Proceedings of the 15th annual conference companion on Genetic and evolutionary computation
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The hydrophobic-polar (HP) model for protein structure prediction abstracts the fact that hydrophobic interactions are a dominant force in the protein folding process. This model represents a hard combinatorial optimization problem, which has been widely addressed using evolutionary algorithms and other metaheuristics. In this paper, the multiobjectivization of the HP model is proposed. This originally single-objective problem is restated as a multiobjective one by decomposing the conventional objective function into two independent objectives. By using different evolutionary algorithms and a large set of test cases, the new alternative formulation was compared against the conventional single-objective problem formulation. As a result, the proposed formulation increased the search performance of the implemented algorithms in most of the cases. Both two- and three-dimensional lattices are considered. To the best of authors' knowledge, this is the first study where multiobjective optimization methods are used for solving the HP model.