摘要
为解决多模式资源约束项目调度问题(MRCPSP),在建立数学模型基础上,提出一种改进的Memetic算法对模型进行求解。该算法利用遗传算法进行全局搜索,采用针对活动执行模式的整数编码方式,基因的值表示活动的优先权和执行模式,每条染色体对应一个满足资源约束的项目调度方案,种群在交叉和变异后采用模拟退火算法进行局部优化。实例仿真结果表明了该算法的有效性和高效性。
To solve the Multi-mode Resource-Constrained Project Scheduling Problem （MRCPSP）, based on the mathematical model of the MRCPSP, a new memetic algorithm was designed. This algorithm combined the crossover and mutation operation of genetic algorithm, and after each crossover and mutation operation, a simulated annealing algorithm was utilized for local search. A special integer coding scheme was used, the gene represented the priority and execution mode of an activity, each chromosome corresponding to a feasible scheduling meeting resource constraints. In the end, the memetic algorithm was verified by using an example, the results showed that the memetic algorithm is feasible and effective.
出处
《沈阳农业大学学报》
CAS
CSCD
北大核心
2011年第6期752-755,共4页
Journal of Shenyang Agricultural University
基金
广东省自然科学基金项目(101754539192000000)
