نشریه بین المللی مهندسی صنایع و تحقیقات تولید
دانشگاه علم و صنعت ایران
سه شنبه 12 خرداد 1405
[Archive]
جلد 37، شماره 2 - ( 3-1405 )
جلد 37 شماره 2 صفحات 122-108 |
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Nemati M, Kargari M, Nikbakhsh E. Stochastic programming and robust optimization approaches for the product mix problem under uncertainty (case study: lubricant refinery). IJIEPR 2026; 37 (2) :108-122
URL: http://ijiepr.iust.ac.ir/article-1-2578-fa.html
URL: http://ijiepr.iust.ac.ir/article-1-2578-fa.html
Stochastic programming and robust optimization approaches for the product mix problem under uncertainty (case study: lubricant refinery). نشریه بین المللی مهندسی صنایع و تحقیقات تولید. 1405; 37 (2) :108-122
چکیده: (127 مشاهده)
Determining optimal product mix under uncertain demand and capacity is a critical challenge in the lubricant industry. This study proposes four MILP models: deterministic, robust scenario-based, downside-risk two-stage stochastic, and CVaR two-stage stochastic. All models incorporate real-world constraints including multi-period, multi-product settings, dual-warehouse inventory, backlog/lost-sale shortages, and mandatory production of unprofitable products. Using real data from a major Iranian lubricant refinery, the models improve profit from the company's actual 300 million monetary units (MU) to 535 (deterministic) and 504 million MU (CVaR). Among stochastic models, the robust approach provides the highest worst-case profit and most stable performance. This is the first systematic comparison of these three stochastic approaches in the lubricant industry under identical constraints, demonstrating the value of uncertainty-aware production planning.
نوع مطالعه: پژوهشي |
موضوع مقاله:
Production Planning & Control
دریافت: 1404/7/22 | پذیرش: 1405/2/27 | انتشار: 1405/3/30
دریافت: 1404/7/22 | پذیرش: 1405/2/27 | انتشار: 1405/3/30
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