مدل بهینه سازی برای برنامه ریزی تولید پالایشگاه سراسری
|کد مقاله||سال انتشار||تعداد صفحات مقاله انگلیسی||ترجمه فارسی|
|10177||2008||4 صفحه PDF||سفارش دهید|
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Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Chinese Journal of Chemical Engineering, Volume 16, Issue 1, February 2008, Pages 67–70
This article addresses a production planning optimization problem of overall refinery. The authors formulated the optimization problem as mixed integer linear programming. The model considers the main factors for optimizing the production plan of overall refinery related to the use of run-modes of processing units. The aim of this planning is to decide which run-mode to use in each processing unit in each period of a given horizon, to satisfy the demand, such as the total cost of production and inventory is minimized. The resulting model can be regarded as a generalized lot-sizing problem where a run-mode can produce and consume more than one product. The resulting optimization problem is large-sized and NP-hard. The authors have proposed a column generation-based algorithm called branch-and-price (BP) for solving the interested optimization problem. The model and implementation of the algorithm are described in detail in this article. The computational results verify the effectiveness of the proposed model and the solution method.
The main aim of production planning is to decide what to produce, how much to produce and when to produce for a given plan horizon in a company. The production plan includes yearly plan, seasonal plan and monthly plan in terms of time horizon. The objective of production planning in a refinery is to generate as many valuable products as possible, such as gasoline, jet fuel, diesel, and so on, and at the same time satisfying market demand and other constraints. Oil refining is one of the most complex chemical industries, which involves many different and complicated processes with various possible connections. It is well known that the oil refining is a typical continuous production process. Maybe a typical refinery includes tens of units. Therefore the optimization of the production planning of the overall refinery is considered as one of the most difficult and challenging tasks, which is also often formidable, even impossible [l]. Nevertheless, the production plan optimization is an important profit growth point thus it also becomes a burning hot topic in both industry and academia. Various optimization models have been developed for individual units with specific technological characteristics. However, the optimization of the production units does not achieve the global economic optimization of the plant. Usually the objectives of the individual units are conflicting and many times infeasible thus many production paths are restricted or disabled. The production planning optimization for refinery-wide has been addressed by using linear programming in the past decades. Although the linear programming models are not good enough to consider the discrete features of the planning problem, such as the dynamic feature of demand, uneven features of the supplement of crude oil and the production of processing units interms of time periods. Recent studies for optimization of production planning have been toward the development of nonlinear programming and mixed integer linear programming models 12, 31. The main study of this article is to propose a production planning model and algorithm for refinery-wide optimization.
نتیجه گیری انگلیسی
The production planning optimization for refinerywide is considered as one of the most difficult and challenging tasks. This article has formulated a generalized lot-sizing problem model for the problem for a typical refinery and proposed a branch-and-price algorithm for solving the optimization problem. The computational results show that the proposed model and algorithm are effective. It is promising for improving the production plan of the refinery. The future research directions are expected in continuous time modeling for production plan optimization in refineries.