基于生物激素调控的动态自适应膜进化协同优化算法及应用研究

Considering the increasingly scale and complexity in the optimization problem, how to develop a dynamic optimization algorithm efficiently and quickly is a significant and challenging subject. In the project, we will introduce the hormone regulation to the membrane computing, and propose a dynamic adaptive membrane evolutionary collaborative optimization algorithm based on the hormone regulation. This project will be carried out in four sections: (1) Learning and simulating the information processing regulation of hormone, such as self-adaption, self-organization, self-learning and self-coordination, establishing the dynamic evolutionary rules of membrane structure, and proposing the dynamic adaptive membrane computing model based on the hormone regulation. (2) Using Hill regulation function and the reaction-diffusion model of hormones, integrating the dynamic membrane structure framework and the adaptive swarm intelligent cooperation search algorithm, and proposing a dynamic adaptive membrane evolutionary collaborative optimization algorithm based on hormone regulation. (3) Applying the dynamic membrane collaborative optimization algorithm to solve DNA encoding and the large-scale optimization problems in economic social system. (4) Designing the simulation software of the proposed algorithm, and establishing the large-scale optimization simulation platform.

面对日益庞大的问题规模及复杂性，如何构建快速高效的动态优化算法是一个非常有意义和极具挑战的课题。本项目拟将生物激素调控机制引入膜计算，研究基于生物激素调控的动态自适应膜进化协同进化算法。项目研究主要内容包括：（1）借鉴和模拟生物激素内在蕴含的自适应性、自组织、自学习、自协调等信息处理机制，建立膜结构动态演化规则，构建基于生物激素调控的动态自适应膜计算新型模型；（2）利用Hill调节函数和激素反应扩散模型，融合动态膜结构框架和自适应群集智能协同搜索算法，构建基于生物激素调控的动态自适应膜进化协同优化算法；（3）利用动态自适应膜进化协同优化算法，求解DNA编码、大规模经济社会优化等问题；（4）开发基于动态自适应膜进化算法的大规模优化仿真平台，建立其大规模优化实现平台。

在膜进化算法中，如何构建快速高效的动态膜优化算法是一个非常有意义和极具挑战的课题。本项目将生物激素调控机制引入膜计算，研究基于生物激素调控的动态自适应膜进化协同进化算法。本项目取得了丰富的研究成果，相继在《IEEE Transactions on Cybernetics》、《IEEE Transactions on Industrial Informatics》、《IEEE Transactions on Intelligent Transportation Systems》、《IEEE Transactions on NanoBioscience》、《Engineering Applications of Artificial Intelligence》、《Journal of Cleaner Production》、《Information Sciences》、《Knowledge-Based Systems》、《Swarm and Evolutionary Computation》、《Expert Systems with Application》、《International Journal of Parallel, Emergent and Distributed Systems》等期刊发表论文20篇。具体说来，项目成果主要包括四个方面。一是借鉴和模拟生物激素的信息处理机制，研究了基于生物激素调控的动态自适应膜计算新型模型；二是利用Hill调节函数，融合动态膜结构框架和差分进化算法，构建基于生物激素调控的动态自适应膜进化协同优化算法；三是提出了改进的膜进化协同优化算法，求解车辆路径优化、约束工程设计等现实问题；四是拓展膜计算研究领域，提出了基于细胞迁移的智能决策膜系统。