二进制中心引力优化算法及其在非线性0-1规划中的应用

Binary central force optimization algorithm and its application in nonlinear 0-1 programming

为求解非线性0-1规划问题,提出了一种二进制中心引力优化算法。根据引力计算加速度,利用加速度更新位置,采用转换函数实现连续的位置变量到离散的0-1变量的变换。采用典型的非线性0-1规划测试问题进行数值实验,并将算法与二进制粒子群优化算法和二进制引力搜索算法进行比较。实验结果表明,在解的稳定性和计算精度两个方面给出的算法具有显著优势,为非线性0-1规划问题的求解提供了新方法。

To solve nonlinear 0-1 programming problems, this paper proposed a binary CFO （BCFO）. It used the gravitation- al force to calculate the acceleration of the object, and employed the acceleration to update the position. To transform from the continuous position variables to discrete 0-1 variables, it adopted transfer functions, and used the benchmarks of nonlinear 0-1 programming problems to perform numerical experiments. It implemented performance comparison of BCFO, binary particle swarm optimization algorithm, and binary gravitational search algorithm using the set of benchmark test problems. The experi- mental results demonstrate that the proposed algorithm has significant advantages in the stability of solutions and computational accuracy. This paper provides a new method to solve the nonlinear 0-1 programming problems.