PDoublePop: An implementation of parallel genetic algorithm for function optimization

A software for the implementation of parallel genetic algorithms is presented in this article. The underlying genetic algorithm is aimed to locate the global minimum of a multidimensional function inside a rectangular hyperbox. The proposed software named PDoublePop implements a client–server model for parallel genetic algorithms with advanced features for the local genetic algorithms such as: an enhanced stopping rule, an advanced mutation scheme and periodical application of a local search procedure. The user may code the objective function either in C++ or in Fortran77. The method is tested on a series of well-known test functions and the results are reported.本文介绍了一款用于实现并行遗传算法的软件。该软件所依托的遗传算法旨在求解矩形超盒（rectangular hyperbox）内多维函数的全局最小值。本文提出的这款名为PDoublePop的软件采用客户端-服务器（client–server）模型实现并行遗传算法，并为局部遗传算法配备了多项高级特性：包括改进的停止准则、优化的变异策略，以及周期性执行的局部搜索流程。用户可通过C++或Fortran77编写目标函数。本文通过一系列经典测试函数对该方法进行了测试，并给出了对应的测试结果。