提出利用混合P2P(Mixed Peer to Peer)架构结合MA(Mobile Agent)技术解决移动计算环境下数据可靠收敛问题,在此基础上建立了MAMP(Mobile Agent and Mixed Peer Model)模型。分析了模型的系统结构和核心技术,重点阐述了MAMP模型的同步策...提出利用混合P2P(Mixed Peer to Peer)架构结合MA(Mobile Agent)技术解决移动计算环境下数据可靠收敛问题,在此基础上建立了MAMP(Mobile Agent and Mixed Peer Model)模型。分析了模型的系统结构和核心技术,重点阐述了MAMP模型的同步策略——HVU(Highest Votes to Update)算法,给出了严格的数学证明。实验结果表明,该模型基础下的算法具有较高的可靠性。展开更多
A memetic algorithm （MA） for a multi-mode resourceconstrained project scheduling problem （MRCPSP） is proposed. We use a new fitness function and two very effective local search procedures in the proposed MA. The f...A memetic algorithm （MA） for a multi-mode resourceconstrained project scheduling problem （MRCPSP） is proposed. We use a new fitness function and two very effective local search procedures in the proposed MA. The fitness function makes use of a mechanism called ＂strategic oscillation＂ to make the search process have a higher probability to visit solutions around a ＂feasible boundary＂. One of the local search procedures aims at improving the lower bound of project makespan to be less than a known upper bound, and another aims at improving a solution of an MRCPSP instance accepting infeasible solutions based on the new fitness function in the search process. A detailed computational experiment is set up using instances from the problem instance library PSPLIB. Computational results show that the proposed MA is very competitive with the state-of-the-art algorithms. The MA obtains improved solutions for one instance of set J30.展开更多
文摘提出利用混合P2P(Mixed Peer to Peer)架构结合MA(Mobile Agent)技术解决移动计算环境下数据可靠收敛问题,在此基础上建立了MAMP(Mobile Agent and Mixed Peer Model)模型。分析了模型的系统结构和核心技术,重点阐述了MAMP模型的同步策略——HVU(Highest Votes to Update)算法,给出了严格的数学证明。实验结果表明,该模型基础下的算法具有较高的可靠性。
基金supported by the National Natural Science Foundation of China(71171038)
文摘A memetic algorithm （MA） for a multi-mode resourceconstrained project scheduling problem （MRCPSP） is proposed. We use a new fitness function and two very effective local search procedures in the proposed MA. The fitness function makes use of a mechanism called ＂strategic oscillation＂ to make the search process have a higher probability to visit solutions around a ＂feasible boundary＂. One of the local search procedures aims at improving the lower bound of project makespan to be less than a known upper bound, and another aims at improving a solution of an MRCPSP instance accepting infeasible solutions based on the new fitness function in the search process. A detailed computational experiment is set up using instances from the problem instance library PSPLIB. Computational results show that the proposed MA is very competitive with the state-of-the-art algorithms. The MA obtains improved solutions for one instance of set J30.
