Biologically-implemented Genetic Algorithm for Protein Engineering

Hiroshi Someya, Kensaku Sakamoto, and Masayuki Yamamura

In Proceedings of ACM Genetic and Evolutionary Computation Conference: GECCO-2009, pp.233-240, doi:10.1145/1569901.1569934, Montreal, Canada (July 2009).

Abstract: Protein engineering, developing novel proteins with a desired activity, has become increasingly important in many fields. This paper presents two studies in protein engineering: (i) a biological implementation of a genetic algorithm, with an observed in vitro evolution, and (ii) its preliminary computer simulation using a prototypical probabilistic model based on a random walk. The steady evolution of the fitness distribution of the mutant proteins that appeared in the biological experiments has provided some convincing evidence about the search behavior and the fitness landscape. The computer simulation and the simple probabilistic model have indicated their future potential for providing a practical alternative to the time-consuming manual operations in the biological experiments. Successful experimental results in the two studies have raised expectations of their further development and mutually beneficial interactions.

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Parameter Tuning of Real-valued Crossover Operators for Statistics Preservation

Hiroshi Someya

Lecture Notes in Computer Science 5361 Simulated Evolution and Learning (Proceedings of The Seventh International Conference on Simulated Evolution And Learning: SEAL2008), pp.269–278, doi:10.1007/978-3-540-89694-4_28, Melbourne, Australia (December 2008).

Abstract: Parameters of real-valued crossover operators have been often tuned under a constraint for preserving statistics of infinite parental population. For applications in actual scenes, in a previous study, an alternative constraint, called unbiased constraint, considering finiteness of the population has been derived. To clarify the wide applicability of the unbiased constraint, this paper presents two additional studies: (1) applying it to various crossover operators in higher dimensional search space, and (2) generalization of it for preserving statistics of overall population. Appropriateness of the parameter setting based on the unbiased constraint has been supported in discussion on robust search.

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Cautious Particle Swarm

Hiroshi Someya

In Proceedings of IEEE Swarm Intelligence Symposium: SIS2008, in CD-ROM, doi:10.1109/SIS.2008.4668292, St. Louis, Missouri, USA (September 2008).

Abstract: Behavior and search performance of the proposed cautious particle swarm, in which the particles are cautious about imitating the best successful one, are investigated with a question: “Is it really the best strategy for a group that every individual in which obediently imitates the top one?” Their neutral or disobedient attitudes to the global best are expressed by replacing the conventional uniform distribution for random numbers with either of the two probability distributions: slided uniform distribution and asymmetrical normal distribution. Empirical analyses on the behavior of such a single particle in one-dimensional search space have aroused an expectation that appropriate cautiousness balance may accomplish both exploration-oriented search for avoiding local minima and exploitation-oriented search for finding the global optimum near the global best. For discussion on the optimization performance of the cautious particle swarm, experiments in typical test functions were performed. The experimental results have presented an acceptable parameter range of obedience for appropriate cautiousness.

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Theoretical Parameter Value for Appropriate Population Variance of the Distribution of Children in Real-coded GA

Hiroshi Someya

In Proceedings of IEEE Congress on Evolutionary Computation: CEC2008 (IEEE World Congress on Computational Intelligence: WCCI2008), pp.2722–2729, doi:10.1109/CEC.2008.4631163, Hong Kong (June 2008).

Abstract: The purposes of this paper are to discuss theoretical parameter value for crossover operators in real-coded GAs (RCGAs) and to bridge the gap between earlier related studies. Crossover operator in RCGAs has at least one parameter that forms its probability distribution function. The appropriateness of the value for this parameter affects optimization performance of RCGA. To obtain suitable parameter value, some manners have been reported. However, they have confused us by their several differences, such as the reference point often used as the first choice to be tuned. This paper has theoretically introduced a constraint that explains that these manners are essentially identical. Parameter values determined under this constraint have been empirically confirmed that they satisfy requirements of the manners. Experiments on several test functions have supported that such parameter values are suitable for the reference point.

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Theoretical Analysis on an Inversion Phenomenon of Convergence Velocity in a Real-Coded GA

Hiroshi Someya

In Proceedings of IEEE Congress on Evolutionary Computation; CEC2007, pp. 4531–4537, doi:10.1109/CEC.2007.4425065, Singapore (September 2007).

Abstract: The aims of this paper are to analyze an inversion phenomenon theoretically and discussion on appropriateness of combination of a crossover operator and a selection model. In the previous study, the author designed a crossover operator that worked well on various kinds of objective functions. One of the features of the objective functions is “the optimum exists near a boundary much more than the other.” On such objective functions, with recommended selection model, the proposed crossover operator set with an appropriate parameter has shown the fastest convergence speed. However, with another selection model, its convergence speed has been the slowest. In order to understand this inversion phenomenon, a theoretical analysis quantified the selection pressures of the selection models and estimated the expected positions of the center of gravity of the population. The theoretical results corresponded to empirical verifications and successfully explained. Finally, a guideline for designing RCGAs was obtained.

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