کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
4942935 1437615 2018 12 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Optimization of fed-batch fermentation processes using the Backtracking Search Algorithm
ترجمه فارسی عنوان
بهینه سازی فرایندهای تخمیر تغذیه دسته ای با استفاده از الگوریتم جستجوی عقبگرد
کلمات کلیدی
تخمیر تغذیه دسته ای؛ الگوریتم جستجوی عقبگرد؛ الگوریتم های تکاملی؛ تصفیه فاضلاب؛ بهینه سازی مسیر تغذیه؛ لجن فاضلاب
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
چکیده انگلیسی


- Optimizations in winery wastewater and sewage sludge treatment are tackled.
- Recent metaheuristics namely CMAES, BSA and DE are found to give competent results.
- Improved DE metaheuristic, BSA gives best overall performance for all problems.

Fed-batch fermentation has gained attention in recent years due to its beneficial impact in the economy and productivity of bioprocesses. However, the complexity of these processes requires an expert system that involves swarm intelligence-based metaheuristics such as Artificial Algae Algorithm (AAA), Artificial Bee Colony (ABC), Covariance Matrix Adaptation Evolution Strategy (CMAES) and Differential Evolution (DE) for simulation and optimization of the feeding trajectories. DE traditionally performs better than other evolutionary algorithms and swarm intelligence techniques in optimization of fed-batch fermentation. In this work, an improved version of DE namely Backtracking Search Algorithm (BSA) has edged DE and other recent metaheuristics to emerge as superior optimization method. This is shown by the results obtained by comparing the performance of BSA, DE, CMAES, AAA and ABC in solving six fed batch fermentation case studies. BSA gave the best overall performance by showing improved solutions and more robust convergence in comparison with various metaheuristics used in this work. Also, there is a gap in the study of fed-batch application of wastewater and sewage sludge treatment. Thus, the fed batch fermentation problems in winery wastewater treatment and biogas generation from sewage sludge are investigated and reformulated for optimization.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Expert Systems with Applications - Volume 91, January 2018, Pages 286-297
نویسندگان
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