Applications of Genetic Algorithms in Chemical Engineering II: Case Studies

2014 ◽  
pp. 61-87 ◽  
Author(s):  
Santosh K. Gupta ◽  
Manojkumar Ramteke
Keyword(s):  
Genetic Algorithms ◽  
Case Studies ◽  
Chemical Engineering

Naive models as active expert system in bioengineering and chemical engineering

1988 ◽  
Vol 53 (7) ◽  
pp. 1476-1499 ◽  
Author(s):  
Mirko Dohnal
Keyword(s):  
Expert System ◽  
Case Studies ◽  
Chemical Engineering ◽  
Anaerobic Fermentation ◽  
Continuous Fermentation ◽  
Point Of View ◽  
Qualitative Variable ◽  
Human Thinking

A possibility of qualitative variable utilization for description and evaluation of phenomena and processes from non-formal human thinking point of view is presented. Paper gives methods of naïve modelling and realistically assesses results that can be awaited. The method is demonstrated on two case studies that are given in full details, namely continuous fermentation (fermentor, two separators) and anaerobic fermentation.

scholarly journals Ecosystem Management and Ecological Modeling

2002 ◽  
Vol 2 ◽  
pp. 107-121 ◽  
Author(s):  
S.E. JØrgensen
Keyword(s):  
Case Studies ◽  
Ecosystem Management ◽  
Chemical Engineering ◽  
Ecological Engineering ◽  
Ecological Modeling ◽  
Environmental Problems ◽  
Point Of View ◽  
Good Knowledge ◽  
Environmental Technology ◽  
System Properties

It is the intention of this paper to demonstrate that environmental technology must be supplemented by other tools to be able to solve environmental problems properly. Five cases are used to illustrate the possibilities of ecological engineering, a new engineering field based on ecology, as chemical engineering is based on chemistry. It encompasses restoration of ecosystems, utilization of ecosystems to the benefit of both mankind and nature, construction of ecosystems, and ecologically sound planning of ecosystems from a holistic point of view. Ecological engineering requires a good knowledge of the system properties of ecosystems to be able to fully utilize the possibilities that ecosystem management offers. Models reflecting the ecosystem properties are furthermore needed to be able to quantify the effects of the ecological engineering solutions to the environmental problems. This is clearly demonstrated in two of the five case studies presented in the paper.

A Study on Evolutionary Technique to Predict the Sales During COVID-19

2021 ◽  
pp. 376-402
Author(s):  
Manu PriyaDarshani ◽  
Mohan Prasad Sinha ◽  
Keshav Sinha
Keyword(s):  
Growth Rate ◽  
Genetic Algorithms ◽  
Case Studies ◽  
Indian Market ◽  
Heavy Industry ◽  
Traditional Methods ◽  
Sales Prediction ◽  
Enormous Amount ◽  
Evolutionary Technique

COVID-19 has affected the growth of every industry; in the meantime, an enormous amount of demand is present in the field of telecom and automobiles. In this chapter, the authors present case studies based on sales prediction for the Indian market. The analysis of the study is based on the various traditional methods like growth rate (GR), percentage growth rate (PGR), and the evolutionary techniques like genetic algorithms (GA). The data are collected for the report of telecommunication and heavy industry ministry (Republic of India). The results are used to analyze the sale of automobiles and telecommunication devices and to predict the growth at the time of the COVID-19 pandemic. The prediction is used to identify the upcoming sale and counterparts with demand.

scholarly journals A Novel Method for Obtaining the Signature of Household Consumer Pairs

Energies ◽  
2020 ◽  
Vol 13 (22) ◽  
pp. 6030
Author(s):  
Dadiana-Valeria Căiman ◽  
Toma-Leonida Dragomir
Keyword(s):  
Genetic Algorithms ◽  
Case Studies ◽  
Nonlinear Regression ◽  
Power Level ◽  
Electricity Consumption ◽  
The Other ◽  
Total Current ◽  
Novel Method

The management of electricity consumption by household consumers requires multiple ways of consumer monitoring. One of these is the signature i(v) determined by monitoring the consumer voltage-current trajectory. The paper proposes a novel method for obtaining signatures of 2-multiple consumers, i.e., a pair of consumers connected in parallel. Signatures are obtained from samples of the voltage at the consumers’ terminals and of the total current absorbed by the consumers, measured at a frequency of only 20 Hz. Within the method, signatures are calculated using genetic algorithms (GA) and nonlinear regression, according to a procedure developed by the authors in a previous paper. The management of the data selected for the signature assignment represents the novelty. The method proposed in this paper is applied in two case studies, one concerning household consumers within the same power level, the other for household consumers of different power levels. The results confirm the possibility of obtaining signatures of i(v) type.

scholarly journals Mobile learning in chemical engineering: An outlook based on case studies

2021 ◽  
Vol 35 ◽  
pp. 132-145
Author(s):  
Guillermo Díaz-Sainz ◽  
Gema Pérez ◽  
Lucía Gómez-Coma ◽  
Victor Manuel Ortiz-Martínez ◽  
Antonio Domínguez-Ramos ◽  
...  
Keyword(s):  
Case Studies ◽  
Mobile Learning ◽  
Chemical Engineering

scholarly journals Comparison of MINLP formulations for global superstructure optimization

2022 ◽  
Author(s):  
Jannik Burre ◽  
Dominik Bongartz ◽  
Alexander Mitsos
Keyword(s):  
Case Studies ◽  
Chemical Engineering ◽  
Optimization Problems ◽  
Production Costs ◽  
Continuous Variables ◽  
Equilibrium Constraints ◽  
Problem Size ◽  
Nonconvex Functions ◽  
Computational Performance ◽  
Problem Formulations

AbstractSuperstructure optimization is a powerful but computationally demanding task that can be used to select the optimal structure among many alternatives within a single optimization. In chemical engineering, such problems naturally arise in process design, where different process alternatives need to be considered simultaneously to minimize a specific objective function (e.g., production costs or global warming impact). Conventionally, superstructure optimization problems are either formulated with the Big-M or the Convex Hull reformulation approach. However, for problems containing nonconvex functions, it is not clear whether these yield the most computationally efficient formulations. We therefore compare the conventional problem formulations with less common ones (using equilibrium constraints, step functions, or multiplications of binary and continuous variables to model disjunctions) using three case studies. First, a minimalist superstructure optimization problem is used to derive conjectures about their computational performance. These conjectures are then further investigated by two more complex literature benchmarks. Our analysis shows that the less common approaches tend to result in a smaller problem size, while keeping relaxations comparably tight—despite the introduction of additional nonconvexities. For the considered case studies, we demonstrate that all reformulation approaches can further benefit from eliminating optimization variables by a reduced-space formulation. For superstructure optimization problems containing nonconvex functions, we therefore encourage to also consider problem formulations that introduce additional nonconvexities but reduce the number of optimization variables.

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