دانلود مقاله ISI انگلیسی شماره 84041
ترجمه فارسی عنوان مقاله

بررسی سیاست های تخصیص مواد ساختمانی: یک روش بهینه سازی شبیه سازی

عنوان انگلیسی
Study on construction material allocation policies: A simulation optimization method
کد مقاله سال انتشار تعداد صفحات مقاله انگلیسی
84041 2018 12 صفحه PDF
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Automation in Construction, Volume 90, June 2018, Pages 201-212

ترجمه کلمات کلیدی
مصالح ساختمانی، تخصیص مواد، دوباره پر کردن موجودی، بهینه سازی شبیه سازی، الگوریتم ژنتیک،
کلمات کلیدی انگلیسی
Construction material; Material allocation; Inventory replenishment; Simulation optimization; Genetic algorithm;
پیش نمایش مقاله
پیش نمایش مقاله  بررسی سیاست های تخصیص مواد ساختمانی: یک روش بهینه سازی شبیه سازی

چکیده انگلیسی

Due to uncertainty in both demand and supply, material shortages are difficult to completely avoid. To reduce the effect on the schedule and cost performance of construction projects, managers should allocate limited material among activities effectively. Motivated by observations of construction practices, this paper investigates the integration of supply logistics and site logistics issues and develops a framework to model inventory replenishment and allocation decisions jointly. On the basis of the activity feature information (e.g., schedule, cost, and demand), we propose five allocation policies to support the integrated inventory management process: schedule-based, cost-based, demand-based, schedule-cost-based, and schedule-demand-based policies. Meanwhile, a genetic algorithm (GA)-based simulation optimization method is utilized to solve the integrated inventory model and find the optimal inventory level under a given allocation policy. Based on a large set of fictitious project networks with different path difference (PD), a computational analysis is conducted to make detailed interpolicy comparisons. It is shown that for a project network with a small (or large) PD value, the schedule-based (or schedule-cost-based) policy is the most appropriate choice.