دانلود مقاله ISI انگلیسی شماره 8108
عنوان فارسی مقاله

# مدل موجودی تولید با تولید فازی و تقاضا با استفاده از معادله دیفرانسیل فازی: بازه مقایسه ای با رویکرد الگوریتم ژنتیک

کد مقاله سال انتشار مقاله انگلیسی ترجمه فارسی تعداد کلمات
8108 2013 13 صفحه PDF سفارش دهید 11493 کلمه
خرید مقاله
پس از پرداخت، فوراً می توانید مقاله را دانلود فرمایید.
عنوان انگلیسی
A production inventory model with fuzzy production and demand using fuzzy differential equation: An interval compared genetic algorithm approach
منبع

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

Journal : Engineering Applications of Artificial Intelligence, Volume 26, Issue 2, February 2013, Pages 766–778

کلمات کلیدی
- تولید فازی - تقاضا فازی - معادلات دیفرانسیل فازی - ادغام ریمان فازی
کلمات کلیدی انگلیسی
پیش نمایش مقاله

#### چکیده انگلیسی

In this paper, a production inventory model, specially for a newly launched product, is developed incorporating fuzzy production rate in an imperfect production process. Produced defective units are repaired and are sold as fresh units. It is assumed that demand coefficients and lifetime of the product are also fuzzy in nature. To boost the demand, manufacturer offers a fixed price discount period at the beginning of each cycle. Demand also depends on unit selling price. As production rate and demand are fuzzy, the model is formulated using fuzzy differential equation and the corresponding inventory costs and components are calculated using fuzzy Riemann-integration. α-cutα-cut of total profit from the planning horizon is obtained. A modified Genetic Algorithm (GA) with varying population size is used to optimize the profit function. Fuzzy preference ordering (FPO) on intervals is used to compare the intervals in determining fitness of a solution. This algorithm is named as Interval Compared Genetic Algorithm (ICGA). The present model is also solved using real coded GA (RCGA) and Multi-objective GA (MOGA). Another approach of interval comparison–order relations of intervals (ORI) for maximization problems is also used with all the above heuristics to solve the model and results are compared with those are obtained using FPO on intervals. Numerical examples are used to illustrate the model as well as to compare the efficiency of different approaches for solving the model.