利用共生生物搜索优化多目标条件下的资源均衡问题

D. Prayogo, Christianto Tirta Kusuma
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引用次数: 6

摘要

糟糕的调度和资源管理可能导致延迟或成本超支。为了避免这些问题,优化解决资源均衡是必要的。几个客观标准被用来解决资源均衡问题。它们的目标是一致的,都是为了减少项目资源需求的波动。本研究比较粒子群优化(PSO)和共生生物搜索(SOS)在解决资源均衡问题时的性能,以找出哪一种方法能产生更好的解决方案。结果表明,SOS比PSO产生更好的解,其中一个目标函数在解决资源均衡问题上优于其他目标函数。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Optimization of resource leveling problem under multiple objective criteria using a symbiotic organisms search
Bad scheduling and resource management can cause delays or cost overruns. Optimization in solving resource leveling is necessary to avoid those problems. Several objective criteria are used to solve resource leveling. Each of them has the same objective, which is to reduce the fluctuation of resource demand of the project. This study compares the performance of particle swarm optimization (PSO) and symbiotic organisms search (SOS) in solving resource leveling problems using separate objective functions in order to find which one produces a better solution. The results show that SOS produced a better solution than PSO, and one objective function is better in solving resource leveling than the others.
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