基于搜索+调整的两阶段萤火虫算法求解机组组合问题

提出了一种新颖的基于搜索+调整的两阶段萤火虫算法求解机组组合问题。算法将机组组合求解流程分解为具有离散变量和连续变量的两个优化问题，通过二进制编码的萤火虫算法求解含离散变量的机组启停主问题，利用改进的实数编码萤火虫算法解决连续变量的负荷经济分配子问题，采用调整策略校核和修复约束，实现主子问题的交替迭代求解。算法通过启发式的约束调整策略，以及两种编码方式实现了离散变量和连续变量的分解优化，提高了机组组合问题求解的效率和精度。通过对6个不同规模算例的计算及与其他经典算法的对比，验证了所提算法的有效性和优越性。

A two-stage firefly algorithm based on search + adjustment for solving unit commitment problem

This paper proposes a novel two-stage firefly algorithm based on search + adjustment for solving unit commitment problem. The solving process of UC will be broken down into two optimization problems with discrete and continuous variables respectively. The main discrete problem to determine the off/on status is solved by binary encoding firefly algorithm, the continuous sub-problem of economic load variables assignment is solved by improved real-coded firefly algorithm, and check and repair constraints are used to achieve alternative and iterative calculation. Heuristic constraints adjustment, as well as two-stage coding approach is used to achieve the decompose optimization of discrete and continuous variables, and improve the efficiency and accuracy of the algorithm. The algorithm proposed is applied to six different systems and compared with classical algorithms, the results verify the effectiveness and superiority. This work is supported by National Natural Science Foundation of China (No. 51477121).