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中文摘要：
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。
英文摘要：
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.
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