ترکیب بهینه پیش بینی در زنجیره تأمین چهار سطحی با هدف کمینه نمودن اثر شلاق چرمی

نوع مقاله: مقاله پژوهشی

نویسندگان

1 گروه مهندسی صنایع، دانشکده فنی مهندسی، دانشگاه آزاد اسلامی واحد لاهیجان، لاهیجان، ایران

2 مهندسی صنایع، دانشکده فنی مهندسی، دانشگاه پیام نور، واحد تهران شمال

3 گروه مهندسی صنایع، دانشکده فنی و مهندسی دانشگاه پیام نور ، تهران، ایران

چکیده

اثر شلاق چرمی که در زنجیره اتفاق می افتد، منجر به ناکارآمدی‌هایی همچون موجودی اضافی و سفارشات عقب افتاده در طول زنجیره می‌گردد. انجام پیش‌بینی مناسب می تواند تا حدود زیادی این مشکلات را مرتفع سازد. با توجه به اینکه زنجیره تأمین دارای سطوح مختلفی می‌باشد، لازم است پیش‌بینی در هر سطحی از زنجیره انجام شود. این مقاله به بررسی مسأله ترکیب بهینه پیش بینی جهت کاهش اثر شلاق چرمی در زنجیره تأمین چهار سطحی می پردازد. برای این منظور یک زنجیره تأمین چهار سطحی در نظر گرفته شده است که در هر یک از سطوح آن، یکی از روش-های میانگین متحرک، هموارسازی نمایی، رگرسیون خطی و شبکه عصبی مصنوعی پرسپترون چند لایه را برای پیش بینی مورد استفاده قرار می-دهد. برای این منظور نخست نسبت به شبیه سازی زنجیره تأمین مورد نظر اقدام و سپس نتایج با استفاده از روش تحلیل واریانس مورد آزمون قرار گرفته‌اند.
از بین ترکیبات، دو ترکیب روش‌های پیش‌بینی با کمترین اثر شلاق چرمی بدست آمده است. میانگین متحرک، شبکه عصبی، هموارسازی نمایی و رگرسیون خطی به ترتیب برای سطح های خرده فروش، عمده فروش، تولید کننده و تامین کننده به عنوان یک جواب و دیگری به شکل میانگین متحرک، هموار سازی نمایی، شبکه عصبی و رگرسیون خطی با همان ترتیب سطوح یاد شده در زنجیره تامین می‌باشند و ترکیبات دیگر از مطلوبیت کمتری برخوردارند.

کلیدواژه‌ها


عنوان مقاله [English]

Determining the optimal forecasting combination of the four-level supply chain to minimize the bullwhip effect

نویسندگان [English]

  • Maryam Daneshmand-Mehr 1
  • Marzban Najafi 2
  • Ramin Sadeghian 3
1 Industrial Engineering Department, Islamic azad university , branch of Lahijan, Lahijan, Iran
2 Industrial Engineering, Faculty of Engineering, Payame Noor University, Tehran, Iran
3 Industrial Engineering, Payam e Noor University, Tehran, Iran
چکیده [English]

Bullwhip effect that occurs in the chain, leads to inefficiencies such as excess inventory and overdue orders during the chain. These problems can be reduced by appropriate predictions. Forecasting must be done in all levels of a supply chain. This paper addresses the problem of optimal combination of forecasting to reduce the bullwhip effect in the four-level supply chain. For this purpose, a four-level supply chain is considered. One of the methods such as moving average, exponential smoothing, linear regression and multilayer perceptron artificial neural network can be considered for predicting in each level. First, the desired supply chain is simulated for this means. The different combinations of aforementioned forecasting methods are calculated. Then a combination of forecasting methods according to minimized bullwhip effects is selected. Finally, the results are analyzed by variance analysis model. Two combinations have the lowest bullwhip effects. Moving average, neural networks, exponential smoothing and linear regression for levels: retailer, wholesaler, manufacturer and supplier respectively as an answer and the other is: moving averages, exponential smoothing, neural network and linear regression in the same mentioned levels and other combinations have less utility.

کلیدواژه‌ها [English]

  • Bullwhip Effect
  • Constant demand
  • Forecasting methods
  • Four levels supply chain
  • Order point system
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