项目优化调度的病毒协同进化遗传算法

项 目 优 化 调 度 的 病 毒 协 同 进 化 遗 传 算 法 胡仕成1+, 徐晓飞1, 李向阳21( 哈 尔 滨 工 业 大 学 计 算 机 科 学 与 技 术 学 院 ,黑 龙 江 哈 尔 滨 150001)2( 哈 尔 滨 工 业 大 学 管 理 学 院 ,黑 龙 江 哈 尔 滨 150001)A Virus Coevolution Genetic Algorithm for Project Optimization SchedulingHU Shi-Cheng1+, XU Xiao-Fei1, LI Xiang-Yang21(School of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001, China)2(School of Management, Harbin Institute of Technology, Harbin 150001, China)+ Corresponding author: Phn: +86-451-6419787, E-mail: hu_shicheng@yahoo.com.cn, http://www.cs.hit.edu.cnReceived 2002-11-12; Accepted 2003-03-24Hu SC, Xu XF, Li XY. A virus coevolution genetic algorithm for project optimization scheduling. Journal of Software, 2004,15(1):49~57.http://www.jos.org.cn/1000-9825/15/49.htm Abstract: In this paper, a virus coevolution genetic algorithm (multi-mode project scheduling-virus co-evolution genetic algorithm, MPS-VEGA) for the precedence and resource constrained multi-mode project scheduling problem is presented, and the encoding of the solution and the operators such as selection, crossover, mutation and virus_infection are given. MPS-VEGA is used to obtain the optimal scheduling sequences and resource modes for the activities of the project so that the project cost is minimized, which can transmit evolutionary genes not only between parent and child generations vertically by the genetic operators but also in the same generation horizontally by the virus_infection operator so as to perform a global search and a local search, respectively. The schema theorem is adopted to analyze the performance of MPS-VEGA. The theoretical analysis and experimental results show that the...