项目优化调度的多智能体社会进化算法  

A Multi-Agent Social Evolutionary Algorithm for Project Optimization Scheduling

作　　者：潘晓英[1] 焦李成[2] 

机构地区：[1]西安电子科技大学智能信息处理研究所,西安710071 [2]西安电子科技大学智能感知与图像理解教育部重点实验室,西安710071

出　　处：《计算机研究与发展》2008年第6期998-1003,共6页Journal of Computer Research and Development

基　　金：国家自然科学基金项目(60703107,60703108);国家“八六三”高技术研究发展计划基金项目(2006AA01Z107);国家教育部博士点基金项目(20060701007,20070701022);陕西省自然科学基金项目(2007F32)~~

摘　　要：结合多智能体系统、进化算法以及关系网模型,提出了一种多智能体社会进化算法用于求解项目活动的一个最优调度顺序以使整个工程的工期最短.每个智能体生存于环境中,为了增加自身能量将与其邻域展开竞争及协同操作,同时可利用自身的知识进行自学习来增加能量.根据项目优化调度的问题特点,设计了智能体的竞争行为、协同行为以及自学习行为.通过对PSPLIB中的标准问题进行测试,同时与其他启发式算法相比较的仿真实验结果表明该算法具有良好的性能,能在较短的时间内寻找到十分接近"最优解"的调度序列.A multi-agent social evolutionary algorithm for the precedence and resource constrained single-mode project optimization scheduling （RCPSP-MASEA） is proposed. RCPSP-MASEEA is used to obtain the optimal scheduling sequences so that the duration of the project is minimized. With the intrinsic properties of RCPSP in mind, the multi-agent systems, social acquaintance net and evolutionary algorithms are integrated to form a new algorithm. In this algorithm, all agents live in lattice-like environment. Making use of the designed behaviors, RCPSP-MASEA realizes the ability of agents to sense and act on the environment in which they live, and the local environments of all the agents are constructed by social acquaintance net. Based on the characteristics of project optimization scheduling, the encoding of solution＇ the operators such as competitive, crossover and self-learning are given. During the process of interacting with the environment and the other agents, each agent increases energy as much as possible, so that RCPSP-MASEA can find the optima. Through a thorough computational study for a standard set of project instances in PSPLIB, the performance of algorithm is analyzed. The experimental results show RCPSP-MASEA has a good performance and it can reach near-optimal solutions in reasonable times. Compared with other heuristic algorithms, RCPSP-MASEA also has some advantages.

关 键 词：资源受限项目调度 多智能体系统 关系网模型 竞争行为 协作行为 自学习行为 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]