基于元启发式方法的泗水PT X预拌混凝土供应链优化

Daniel Mulyono Kresnadi, D. Prayogo
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引用次数: 0

摘要

随着基础设施的发展,对预拌混凝土(RMC)的需求增加。如果RMC不能按时交付,则会延误施工进度或卡车需要在施工现场等待,因此交付的混凝土如果超过混凝土凝结时间就会失效。本研究采用元启发式方法,基于泗水一家配料厂的实时数据,对现拌混凝土供应链进行了优化。本研究中使用的元启发式方法是粒子群优化(PSO)和共生生物搜索(SOS),并比较了这两种元启发式算法的性能,因为这两种算法都被证明在解决各种优化问题上是有效的。本研究的目标函数是最小化搅拌车的总等待时间。结果表明,SOS算法比PSO算法具有更好的性能,总等待时间为100,863小时。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Supply Chain Optimization of Ready Mix Concrete at PT X in Surabaya Using the Metaheuristic Method
Infrastructure development is followed by an increase in demand for ready-mix concrete (RMC). Some failures in delivering RMC on time would delay construction performance or the truck would need to wait at the construction site, so the delivered concrete became useless if it exceeded the concrete setting time limit. This research optimizes the supply chain of ready mix concrete based on real-time data from a batching plant in Surabaya by using the metaheuristic method. The metaheuristic method used in this research are Particle Swarm Optimization (PSO) and Symbiotic Organisms Search (SOS), and also compares the performance of both metaheuristic algorithms, because both algorithms have proven effective in solving various optimization problems.  The objective function of this research is to minimize the total waiting times of mixer trucks. The results showed that the SOS algorithm has better performance than the PSO algorithm, which gets lower total waiting times of 100,863 hours.
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