Development of an evolutionary algorithm for function optimization problems with an equality constraint and its application to the inference of genetic networks

具有等式约束的函数优化问题的进化算法的开发及其在遗传网络推理中的应用

• 批准号: 23700266
• 负责人: KIMURA Shuhei
• 金额: $ 1.33万
• 依托单位: Tottori University
• 依托单位国家: 日本
• 项目类别: Grant-in-Aid for Young Scientists (B)
• 财政年份: 2011
• 资助国家: 日本
• 起止时间: 2011 至 2013
• 项目状态: 已结题
• 来源: https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-23700266/
• 关键词: 遺伝的アルゴリズム; 遺伝子ネットワーク同定; S-systemモデル; Vohradskyモデル; 進化的アルゴリズム; 遺伝子ネットワーク; 制約付き関数最適化; S-system

In this study, I proposed a technique that makes evolutionary algorithms possible to solve function optimization problems with several inequality and a single equality constraints. The proposed technique simply forces candidate solutions newly generated to satisfy the equality constraint. To generate these candidate solutions, this study uses a Markov chain Monte Carlo method and crossover kernels. This technique is developed for improving the performances of the genetic network inference methods. I found however that, even when the inference of genetic networks is not defined as a function optimization problem without having an equality constraint, reasonable networks are inferred. Thus, this study then proposed two genetic network inference methods that do not use the technique described above.

在这项研究中，我提出了一种技术，使进化算法有可能解决多个不等式和一个单一的等式约束的函数优化问题。 所提出的技术只是迫使新生成的候选解决方案，以满足等式约束。为了生成这些候选解决方案，本研究使用马尔可夫链蒙特卡罗方法和交叉内核。该技术是为了提高遗传网络推理方法的性能而开发的。然而，我发现，即使遗传网络的推理没有被定义为一个没有等式约束的函数优化问题，也可以推断出合理的网络。因此，本研究随后提出了两种不使用上述技术的遗传网络推理方法。

项目成果

Development of an Efficient Parameter Estimation Method for the Inference of Vohradsky's Neural Network Models of Genetic Networks

开发用于遗传网络 Vohradsky 神经网络模型推理的有效参数估计方法

• 发表时间: 2013
• 期刊: Proc. of the 2013 International Joint Conference on Neural Networks
• 作者: S.Kimura;M.Sato and M.Okada-Hatakeyama
• 通讯作者: M.Sato and M.Okada-Hatakeyama

Constrained Multimodal Function Optimization using a Simple Evolutionary Algorithm

使用简单进化算法的约束多峰函数优化

• 发表时间: 2011
• 期刊: Proc. of the 2011 Congress on Evolutionary Computation
• 作者: Yoshifumi Kusunoki;Tetsuzo Tanino;S.Kimura and K.Matsumura
• 通讯作者: S.Kimura and K.Matsumura

遺伝子ネットワークのS-system モデル高速同定法

基因网络S系统模型快速识别方法

• 发表时间: 2011
• 作者: Yoshifumi Kusunoki;Tetsuzo Tanino;木村周平
• 通讯作者: 木村周平

Inference of Vohradský's models of genetic networks by solving two-dimensional function optimization problems.

• DOI: 10.1371/journal.pone.0083308
• 发表时间: 2013
• 期刊: PloS one
• 影响因子: 3.7
• 作者: Kimura S;Sato M;Okada-Hatakeyama M
• 通讯作者: Okada-Hatakeyama M

Inference of S-system Models of Genetic Networks by Solving Linear Programming Problems and Sets of Linear Algebraic Equations

通过求解线性规划问题和线性代数方程组来推断遗传网络的 S 系统模型

• 发表时间: 2012
• 期刊: Proc. of the 2012 International Joint Conference on Neural Networks
• 作者: S.Kimura;K.Matsumura and M.Okada-Hatakeyama
• 通讯作者: K.Matsumura and M.Okada-Hatakeyama