摘要
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.
出处
《计算机应用研究》
CSCD
北大核心
2017年第8期2372-2375,共4页
Application Research of Computers
基金
国家自然科学基金资助项目(71401106)
国家教育部人文社会科学规划项目(16YJA630037)
上海市高原学科建设项目
上海高校青年教师培养计划资助项目(ZZSL15018)
上海理工大学国家级培育青年基金资助项目(16HJPY-QN15)
上海理工大学博士科研启动经费项目(1D-15-303-005)
关键词
中心引力优化算法
转换函数
二进制
确定性
central force optimization algorithm
transfer functions
binary
deterministicness