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A Hybrid Swarm Optimization Algorithm for Complex Assignment Problem

机译:复杂分配问题的混合群优化算法

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The optimization of complex systems, such as production scheduling systems and control systems, often encounters some difficulties, such as largescale, hard to model, time consuming to evaluate, NPhard, multi-modal, uncertain and multi-objective, etc. It is always a hot research topic in academic and engineering fields to propose advanced theory and effective algorithms. As a novel evolutionary computing technique, particle swarm optimization (PSO) is characterized by not being limited by the representation of the optimization problems, and by global optimization ability, which has gained wide attentation and research from both academic and industry fields. The task assignment problem in the enterprise with directed graph model is presented. Task assignment problem with buffer zone is solved via a hybrid PSO algorithm. Simulation result shows that the model and the algorithm are effective to the problem.
机译:诸如生产调度系统和控制系统之类的复杂系统的优化通常会遇到一些困难,例如大规模,难以建模,评估耗时,NPhard,多模态,不确定和多目标等。一个学术和工程领域的热门研究课题,旨在提出先进的理论和有效的算法。作为一种新颖的进化计算技术,粒子群优化(PSO)的特点是不受优化问题的表示和全局优化能力的限制,已引起了学术界和工业界的广泛关注和研究。提出了有向图模型的企业任务分配问题。通过混合PSO算法解决了具有缓冲区的任务分配问题。仿真结果表明,该模型和算法是有效的。

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