A floating-point genetic algorithm for solving the unit commitment problem

This paper proposes a floating-point genetic algorithm (FPGA) to solve the unit commitment problem (UCP). Based on the characteristics of typical load demand, a floating-point chromosome representation and an encoding–decoding scheme are designed to reduce the complexities in handling the minimum up/down time limits. Strategic parameters of the FPGA are characterized in detail, i.e., the evaluation function and its constraints, population size, operation styles of selection, crossover operation and probability, mutation operation and probability. A dynamic combination scheme of genetic operators is formulated to explore and exploit the FPGA in the non-convex solution space and multimodal objective function. Experiment results show that the FPGA is a more effective technique among the various styles of genetic algorithms, which can be applied to the practical scheduling tasks in utility power systems.     

Manufacturing cell formation using similarity coefficients and a parallel genetic TSP algorithm: Formulation and comparison

Many algorithms have been proposed to form manufacturing cells from component routings. However, many of these do not have the capability of solving large problems. We propose a procedure using similarity coefficients and a parallel genetic implementation of a TSP algorithm that is capable of solving large problems of up to 1000 parts and 1000 machines. In addition, we also compare our procedure with many existing procedures using nine well-known problems from the literature.

The results show that the proposed procedure compares well with the existing procedures and should be useful to practitioners and researchers.     

On solving energy-dependent partitioned eigenvalue problem by genetic algorithm: The case of real symmetric Hamiltonian matrices

An energy-dependent partitioning scheme is explored for extracting a small number of eigenvalues of a real symmetric matrix with the help of genetic algorithm. The proposed method is tested with matrices of different sizes (30 × 30 to 1000 × 1000). Comparison is made with Löwdin’s strategy for solving the problem. The relative advantages and disadvantages of the GA-based method are analyzed     

Irn(n=2-25)团簇基态结构的遗传算法研究

用遗传算法结合Gupta紧束缚模型势研究了Irn(n=2-25)团簇的基态结构.分析了Irn(n=2-25)团簇的基态结构随团簇尺寸的变化规律.计算结果表明,Irn(n=2-25)团簇的每个原子的平均束缚能和平均第一近邻随团簇尺寸的增加而增大,以总束缚能的二阶差分为判据,Irn(n=2-25)团簇的幻数是4、7、9、13、15、19、23.     

最优保存遗传算法在最优资产组合计算中的应用

本文基文献 [1]的思路 ,详细论述了利用遗传算法解决有风险控制的最优资产组合问题的具体实现过程 .并论证了用浮点数的方法表示的最优保存遗传算法的全局收敛性     

约束装箱问题的混合遗传算法求解

本将最佳适应法和遗传算法相结合，提出了一种新的启发式混合遗传算法对具有时间约束的装箱问题进行求解，给出了具体的算法步骤，试算结果表明基于启发式算法的混合遗传算法适合于求解各种约束条件下的大规模装箱问题。     

基于遗传算法的二层线性规划问题的求解算法

本研究了下层以最优解返回上层的二层线性规划问题的遗传算法。在提出可行度概念的基础上，构造了二层线性规划上层规划问题的适应度函数，由此设计了求解二层线性规划问题遗传算法。为了提高遗传算法处理约束的能力，在产生初始种群时将随机产生的初始种群变为满足约束的初始种群，从而避免了使用罚函数处理约束带来的困难，最后用实例验证了本提出的二层线性规划的遗传算法的有效性。     

基于遗传算法构建巴耳末公式

基于遗传算法构建了巴耳末公式．通过建立合适的拟合数学模型，用计算机对数学模型进行优化，使之尽可能反映氢原子实际谱线分布，并求出经验常量和拟合公式，最后分析了所得结果．     

Complex genetic evolution of artificial self‐replicators in cellular automata

It is widely believed that evolutionary dynamics of artificial self‐replicators realized in cellular automata (CA) are limited in diversity and adaptation. Contrary to this view, we show that complex genetic evolution may occur within simple CA. The evolving self‐replicating loops (“evoloops”) we investigate exhibit significant diversity in macro‐scale morphologies and mutational biases, undergoing nontrivial genetic adaptation by maximizing colony density and enhancing sustainability against other species. Nonmutable subsequences enable genetic operations that alter fitness differentials and promote long‐term evolutionary exploration. These results demonstrate a unique example of genetic evolution hierarchically emerging from local interactions between elements much smaller than individual replicators. © 2004 Wiley Periodicals, Inc. Complexity 10: 33–39, 2004     

遗传程序设计中分布式染色体的一个应用

对一类遗传程序设计问题，提出了简单等长的分布式染色体，取代复杂变长的树结构染色体，使演化算子操作更方便，个体复杂度得到有效控制．用该染色体形式解决割草问题，分析了分布式染色体带来的一些性质，并给出了很好的计算结果．