CEC 2005 - PDF Preprint Papers

CEC 2005 IEEE Congress on Evolutionary Computation

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CEC
2005
IEEE

187views Artificial Intelligence» more CEC 2005»

A genetic algorithm for energy minimization in bio-molecular systems

13 years 10 months ago

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Energy minimization algorithms for bio-molecular systems are critical to applications such as the prediction of protein folding. Conventional energy minimization methods such as th...

Xiaochun Weng, Lutz Hamel, Lenore M. Martin, Joan ...

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Id	Views	Title	Status

1	187	A genetic algorithm for energy minimization in bio-molecular systems	claim
2	183	Ecology-inspired evolutionary algorithm using feasibility-based grouping for constrained optimization	claim
3	179	CasGP: building cascaded hierarchical models using niching	claim
4	177	Dynamic multi-swarm particle swarm optimizer with local search	claim
5	176	Memory-enhanced univariate marginal distribution algorithms for dynamic optimization problems	claim
6	172	An ant algorithm hyperheuristic for the project presentation scheduling problem	claim
7	168	DynDE: a differential evolution for dynamic optimization problems	claim
8	165	Elitist generational genetic chromodynamics - a new radii-based evolutionary algorithm for multimodal optimization	claim
9	154	Coevolution of neural Go players in a cultural environment	claim
10	154	Sensorimotor experience and its metrics: informational geometry and the temporal horizon	claim
11	154	A study on polynomial regression and Gaussian process global surrogate model in hierarchical surrogate-assisted evolutionary algorithm	claim
12	154	A new representation in evolutionary algorithms for the optimization of bioprocesses	claim
13	151	Designing comminution circuits with a multi-objective evolutionary algorithm	claim
14	149	Efficient global optimization (EGO) for multi-objective problem and data mining	claim
15	146	A parallel Monte Carlo simulation on cluster systems for financial derivatives pricing	claim
16	146	Evolution and prioritization of survival strategies for a simulated robot in Xpilot	claim
17	145	Dynamic niching in evolution strategies with covariance matrix adaptation	claim
18	143	Evolutionary algorithm for noun phrase detection in natural language processing	claim
19	140	Complexity transitions in evolutionary algorithms: evaluating the impact of the initial population	claim
20	139	Dynamic salting route optimisation using evolutionary computation	claim
21	138	A note on the population based incremental learning with infinite population size	claim
22	137	Heterogeneous multiprocessor scheduling with differential evolution	claim
23	136	Making soccer kicks better: a study in particle swarm optimization and evolution strategies	claim
24	135	Hybrid evolutionary static scheduling for heterogeneous systems	claim
25	133	On improving genetic programming for symbolic regression	claim
26	132	Formation of modules in a computational model of embryogeny	claim
27	132	Evolving controllers for simulated car racing	claim
28	131	Constraint quadratic approximation operator for treating equality constraints with genetic algorithms	claim
29	130	Adaptive local search parameters for real-coded memetic algorithms	claim
30	128	FPGA segmented channel routing using genetic algorithms	claim
31	128	A study of dynamic severity in chaotic fitness landscapes	claim
32	127	Real-parameter optimization using the mutation step co-evolution	claim
33	127	Hybrid evolutionary algorithms for constraint satisfaction problems: memetic overkill?	claim
34	127	Graph composition in a graph grammar-based method for automata network evolution	claim
35	125	An empirical analysis of the grouping genetic algorithm: the timetabling case	claim
36	123	Population based incremental learning with guided mutation versus genetic algorithms: iterated prisoners dilemma	claim
37	122	Clustering-based approach to identify solutions for the inference of regulatory networks	claim
38	121	A model-based evolutionary algorithm for bi-objective optimization	claim
39	121	Crossing the fabrication gap: evolving assembly plans to build 3-D objects	claim
40	120	An optimization algorithm for imprecise multi-objective problem functions	claim
41	120	Linear genetic programming using a compressed genotype representation	claim
42	120	Evolving hidden Markov models for protein secondary structure prediction	claim
43	118	Multiobjective financial portfolio design: a hybrid evolutionary approach	claim
44	117	Evolving autonomous agent control in the Xpilot environment	claim
45	116	Geometric landscape of homologous crossover for syntactic trees	claim
46	116	Cultural learning and diversity in a changing environment	claim
47	116	A new approach to dynamics analysis of genetic algorithms without selection	claim
48	115	Automated tile design for self-assembly conformations	claim
49	114	Relationships between internal and external metrics in co-evolution	claim
50	114	Two-layered face detection system using evolutionary algorithm	claim
51	114	Evolving improved incremental learning schemes for neural network systems	claim
52	113	Evolutionary computation variants for cooperative spatial coordination	claim
53	112	A quantitative approach for validating the building-block hypothesis	claim
54	112	Using temporal information distance to locate sensorimotor experience in a metric space	claim
55	112	The emergence of cooperation among agents using simple fixed bias tagging	claim
56	110	Music evolution in a complex system of interacting agents	claim
57	110	Evolutionary Solo Pong players	claim
58	110	Dynamic power minimization during combinational circuit testing as a traveling salesman problem	claim
59	109	On the complexity of overcoming gaps with isotropic mutations and elitist selection	claim
60	109	Revisiting genetic selection in the XCS learning classifier system	claim
61	109	Theoretical comparisons of search dynamics of genetic algorithms and evolution strategies	claim
62	109	DNA implementation of k-shortest paths computation	claim
63	109	Co-evolutionary modular neural networks for automatic problem decomposition	claim
64	108	Empowerment: a universal agent-centric measure of control	claim
65	108	Sequential parameter optimization	claim
66	107	Effects of experience bias when seeding with prior results	claim
67	107	Genetic algorithms with self-organized criticality for dynamic optimization problems	claim
68	107	Final exam scheduler - FES	claim
69	107	On the use of rule-sharing in learning classifier system ensembles	claim
70	106	Multiobjective optimization for dynamic environments	claim
71	105	On the convergence of multi-parent genetic algorithms	claim
72	105	Adaptive cluster covering and evolutionary approach: comparison, differences and similarities	claim
73	105	Nonlinear mapping using particle swarm optimisation	claim
74	104	Statistical optimisation and tuning of GA factors	claim
75	104	Distributed brain modelling by means of hierarchical collaborative coevolution	claim
76	103	Evolution of L-systems for compact virtual landscape generation	claim
77	103	A hybrid approach to parameter tuning in genetic algorithms	claim
78	103	Multiobjective clustering around medoids	claim
79	103	Multi-objective optimisation of the pump scheduling problem using SPEA2	claim
80	102	Performance of aggregation pheromone system on unimodal and multimodal problems	claim
81	102	A hybrid model of evolutionary algorithms and branch-and-bound for combinatorial optimization problems	claim
82	100	Online population size adjusting using noise and substructural measurements	claim
83	99	Parallel evolutionary algorithms on graphics processing unit	claim
84	99	A structure preserving crossover in grammatical evolution	claim
85	99	XCS with computed prediction for the learning of Boolean functions	claim
86	98	Linear equality constraints and homomorphous mappings in PSO	claim
87	98	Incorporating a Metropolis method in a distribution estimation using Markov random field algorithm	claim
88	98	Single parent genetic programming	claim
89	98	XCS with computed prediction in continuous multistep environments	claim
90	97	A simple hybrid evolutionary algorithm for finding Golomb rulers	claim
91	94	Genetic programming approach for fault modeling of electronic hardware	claim
92	94	Evolving dispatching rules for solving the flexible job-shop problem	claim
93	94	Performance evaluation of an advanced local search evolutionary algorithm	claim
94	93	Multidimensional epistasis and the advantage of sex	claim
95	93	Localization using evolution strategies in sensornets	claim
96	93	Enumerating knight's tours using an ant colony algorithm	claim
97	93	Effects of evolutionary and lifetime learning on minds and bodies in an artifical society	claim
98	93	Elevator group supervisory control system using genetic network programming with functional localization	claim
99	92	Evolving binary decision diagrams using implicit neutrality	claim
100	92	Investigating the effect of random noise on the evolution of colour terms	claim
101	91	Modeling and analysis of indirect communication in particle swarm optimization	claim
102	91	Using evolutionary techniques to hunt for snakes and coils	claim
103	91	Multi-objective techniques in genetic programming for evolving classifiers	claim
104	90	Equilibrium selection by co-evolution for bargaining problems under incomplete information about time preferences	claim
105	89	A population-based, steady-state procedure for real-parameter optimization	claim
106	89	A restart CMA evolution strategy with increasing population size	claim
107	89	Theoretical analysis of generalised recombination	claim
108	89	Fast evolution of custom machine representations	claim
109	88	Rank and proximity based crossover (RPC) to improve convergence in genetic search	claim
110	87	Improvements to the scalability of multiobjective clustering	claim
111	86	Complementary selection and variation for an efficient multiobjective optimization of complex systems	claim
112	85	Finding attack strategies for predator swarms using genetic algorithms	claim
113	85	Evolving swarms that build 3D structures	claim
114	84	No free lunch, Kolmogorov complexity and the information landscape	claim
115	84	Accessibility between neutral networks in indirect genotype-phenotype mappings	claim
116	83	The fitness map scheme: application to interactive multifractal image denoising	claim
117	83	ICARUS: intelligent coupon allocation for retailers using search	claim
118	80	COFRE: a fuzzy rule coevolutionary approach for multiclass classification problems	claim
119	79	Coarse graining in an evolutionary algorithm with recombination, duplication and inversion	claim
120	74	A scatter search based optimizer for the registration of 3D surfaces	claim
121	73	Evolving problems to learn about particle swarm and other optimisers	claim

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