دانلود مقاله ISI انگلیسی شماره 50431
ترجمه فارسی عنوان مقاله

دو متا-اکتیویته تنظیم شده با پارامتر برای یک مشکل کنترل موجودی با تخفیف در یک محیط فازی

عنوان انگلیسی
Two parameter-tuned meta-heuristics for a discounted inventory control problem in a fuzzy environment
کد مقاله سال انتشار تعداد صفحات مقاله انگلیسی
50431 2014 21 صفحه PDF
منبع

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

Journal : Information Sciences, Volume 276, 20 August 2014, Pages 42–62

ترجمه کلمات کلیدی
موجودی چند دوره ای چند محصول، نرخ تنزیل فازی، فضای ذخیره سازی فازی، الگوریتم جستجوی هارمونی، بهینه سازی ذرات ذرات، تاگوچی
کلمات کلیدی انگلیسی
Multi-product multi-period inventory; Fuzzy discount rate; Fuzzy storage space; Harmony search algorithm; Particle swarm optimization; Taguchi

چکیده انگلیسی

In this paper, a nearly real-world multi-product, multi-period inventory control problem under budget constraint is investigated, where shortages in combination with backorders and lost sales are considered for each product. The ordered quantities of products are delivered in batch sizes with a known number of boxes, each containing a pre-specified number of products. Some products are purchased under an all unit discount policy, and others are purchased under an incremental quantity discount with fuzzy discount rates. The goal is to find the optimal ordered quantities of products such that not only the total inventory cost but also the required storage space (considered as a fuzzy number) to store the products is minimized. The weighted linear sum of objectives is applied to generate a single-objective model for the bi-objective problem at hand and a harmony search algorithm is developed to solve the complex inventory problem. As no benchmarks are available to validate the obtained results, a particle-swarm optimization algorithm is employed to solve the problem in addition to validate the results given by the harmony search method. The parameters of both algorithms are tuned using both Taguchi and response surface methodology (RSM). Finally, to assess the performance of the proposed algorithms some numerical examples are generated, and the results are compared statistically.