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An Enhanced Invasive Weed Optimization in Resource-Constrained Project Scheduling Problem

机译:资源受限项目调度问题中增强的侵入杂草优化

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In this research, an enhanced invasive weed optimization (EIWO) has been proposed to solve resource-constrained project scheduling problem (RCPSP) which subjects to the makespan minimization. Firstly, a hybrid population initialization method is illustrated to improve the quality of initial solutions. Secondly, to enhance the local exploitation ability, a local search approach is embedded in the spatial dispersal process. Thirdly, an improved competitive exclusion based on acceptance probability is proposed. At the end of this article, EIWO is tested and verified by standard benchmark problems from PSPLIB. Compared with the existing algorithms through computer numerical experiments, the new EIWO algorithm is more effective and efficient in solving RCPSP.
机译:在本研究中,提出了增强的侵入性杂草优化(EIWO)来解决受到Makespan最小化的资源受限的项目调度问题(RCPSP)。首先,说明了混合人口初始化方法以提高初始解决方案的质量。其次,为了提高局部利用能力,在空间分散过程中嵌入了本地搜索方法。第三,提出了基于接受概率的改进的竞争排斥。在本文结束时,通过PSPLIB的标准基准问题测试和验证EIWO。与通过计算机数值实验的现有算法相比,新的Eiwo算法在解决RCPSP方面更有效和有效。

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