Multi-level production planning in a petrochemical industry using elitist Teaching-Learning-Based-Optimization

被引：40

作者：

Kadambur, Rajasekhar ^{[1
]}

Kotecha, Prakash ^{[1
]}

机构：

[1] Indian Inst Technol, Dept Chem Engn, Gauhati 781039, Assam, India

来源：

EXPERT SYSTEMS WITH APPLICATIONS | 2015年 / 42卷 / 01期

关键词：

Combinatorial optimization; Production planning; Teaching Learning Based Optimization; DESIGN; SYSTEMS; MODEL;

D O I：

10.1016/j.eswa.2014.08.006

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The complex nature of the petrochemical industries necessitates an efficient decision on a large number of factors so as to optimally operate a plant. Production planning is an integral part of the petrochemical industry and requires the optimal selection of processes, production levels and products to maximize its profit. Previously an MILP formulation has been proposed for guiding the petrochemical industry development in Saudi Arabia (Alfares & Al-Amer, 2002). In this article, we state the limitations of this formulation and propose an alternate elitist TLBO algorithm based strategy to overcome them. The benefits of this strategy include the determination of better production plans that lead to higher profits and have been demonstrated on the eight case studies in the literature. The proposed strategy is generic and can be applied to determine production plans of multiple levels in various industries. (C) 2014 Elsevier Ltd. All rights reserved.

引用

页码：628 / 641

页数：14

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