کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
1135556 | 956103 | 2008 | 31 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Strategies for multiobjective genetic algorithm development: Application to optimal batch plant design in process systems engineering
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
سایر رشته های مهندسی
مهندسی صنعتی و تولید
پیش نمایش صفحه اول مقاله
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چکیده انگلیسی
This work deals with multiobjective optimization problems using Genetic Algorithms (GA). A MultiObjective GA (MOGA) is proposed to solve multiobjective problems combining both continuous and discrete variables. This kind of problem is commonly found in chemical engineering since process design and operability involve structural and decisional choices as well as the determination of operating conditions. In this paper, a design of a basic MOGA which copes successfully with a range of typical chemical engineering optimization problems is considered and the key points of its architecture described in detail. Several performance tests are presented, based on the influence of bit ranging encoding in a chromosome. Four mathematical functions were used as a test bench. The MOGA was able to find the optimal solution for each objective function, as well as an important number of Pareto optimal solutions. Then, the results of two multiobjective case studies in batch plant design and retrofit were presented, showing the flexibility and adaptability of the MOGA to deal with various engineering problems.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computers & Industrial Engineering - Volume 54, Issue 3, April 2008, Pages 539-569
Journal: Computers & Industrial Engineering - Volume 54, Issue 3, April 2008, Pages 539-569
نویسندگان
A. Dietz, C. Azzaro-Pantel, L. Pibouleau, S. Domenech,