کلمات کلیدی مربوط به کتاب بهینه سازی چند هدفه در مهندسی شیمی: تحولات و کاربردها: شیمی و صنایع شیمیایی، روش های ریاضی و مدل سازی در شیمی
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Wiley; 1 edition (May 28, 2013). — 528 p
For reasons both financial and
environmental, there is a perpetual need to optimize the design
and operating conditions of industrial process systems in order
to improve their performance, energy efficiency, profitability,
safety and reliability. However, with most chemical engineering
application problems having many variables with complex
inter-relationships, meeting these optimization objectives can
be challenging. This is where Multi-Objective Optimization
(MOO) is useful to find the optimal trade-offs among two or
more conflicting objectives
This book provides an overview of the recent developments and
applications of MOO for modeling, design and operation of
chemical, petrochemical, pharmaceutical, energy and related
processes. It then covers important theoretical and
computational developments as well as specific applications
such as metabolic reaction networks, chromatographic systems,
CO2 emissions targeting for petroleum refining units, ecodesign
of chemical processes, ethanol purification and cumene process
design
Multi-Objective Optimization in Chemical Engineering:
Developments and Applications is an invaluable resource for
researchers and graduate students in chemical engineering as
well as industrial practitioners and engineers involved in
process design, modeling and optimization
Table of Contents
Preface
Overview
Introduction
Adrian Bonilla-Petriciolet and Gade Pandu Rangaiah
Optimization and Chemical Engineering
Basic Definitions and Concepts of Multi-Objective
Optimization
Multi-Objective Optimization in Chemical Engineering
Scope and Organization of the Book
Optimization of Pooling Problems for Two Objectives Using the
ε-Constraint Method
Haibo Zhang and Gade Pandu Rangaiah
Introduction
Pooling Problem Description and Formulations
ε-Constraint Method and IDE Algorithm
Application to Pooling Problems
Results and Discussion
Conclusions
Multi-objective Optimization Applications in Chemical
Engineering
Shivom Sharma and Gade Pandu Rangaiah
Introduction
Multi-Objective Optimization Applications in Process Design and
Operation
Multi-Objective Optimization Applications in Petroleum
Refining, Petrochemicals, and Polymerization
Multi-Objective Optimization Applications in the Food Industry,
Biotechnology, and Pharmaceuticals
Multi-Objective Optimization Applications in Power Generation
and Carbon Dioxide Emissions
Multi-Objective Optimization Applications in Renewable
Energy
MOO Applications in Hydrogen Production and Fuel Cells
Conclusions
II Multi-Objective Optimization Developments
Performance Comparison of Jumping-Gene Adaptations of the
Elitist Nondominated Sorting Genetic Algorithm
Shivom Sharma, Seyed Reza Nabavi and Gade Pandu Rangaiah
Introduction
Jumping-Gene Adaptations
Termination Criterion
Constraints Handling and Implementation of Programs
Performance Comparison
Conclusions
Improved Constraint Handling Technique for Multi-objective
Optimization with Application to Two Fermentation
Processes
Shivom Sharma and Gade Pandu Rangaiah
Introduction
Constraint Handling Approaches in Chemical Engineering
Adaptive Constraint Relaxation and Feasibility Approach for
SOO
Adaptive Relaxation of Constraints and Feasibility Approach for
MOO
Testing of MODE-ACRFA
Multi-Objective Optimization of the Fermentation Process
Conclusions
Robust Multi-Objective Genetic Algorithm (RMOGA) with Online
Approximation under Interval Uncertainty
Weiwei Hu, Adeel Butt, Ali Almansoori, Shapour Azarm and Ali
Elkamel
Introduction
Background and Definition
Robust Multi-Objective Genetic Algorithm (RMOGA)
Online Approximation-Assisted RMOGA
Case Studies
Conclusion
Chance Constrained Programming to Handle Uncertainty in
Nonlinear Process Models
Kishalay Mitra
Introduction
Uncertainty Handling Techniques
Chance-Constrained Programming: Fundamentals
Industrial Case Study: Grinding
Conclusion
Fuzzy Multi-objective Optimization for Metabolic Reaction
Networks by Mixed-Integer Hybrid Differential Evolution
Feng-Sheng Wang and Wu-Hsiung Wu
Introduction
Problem Formulation
Optimality
Mixed-Integer Hybrid Differential Evolution
Examples
Summary
III Chemical Engineering Applications
Parameter Estimation in Phase Equilibria Calculations using
Multi-Objective Evolutionary Algorithms
Sameer Punnapala, Francisco M. Vargas and Ali Elkamel
Introduction
icle Swarm Optimization (PSO)
Parameter Estimation in Phase Equilibria Calculations
Model Description
Multi-Objective Optimization Results and Discussions
Conclusions
Phase Equilibrium Data Reconciliation using Multi-Objective
Differential Evolution with Tabu List
A. Bonilla-Petriciolet, Shivom Sharma and Gade Pandu
Rangaiah
Introduction
Formulation of the Data-Reconciliation Problem for Phase
Equilibrium Modeling
Multi-Objective Optimization using Differential Evolution with
Tabu List
Data Reconciliation of Vapor-Liquid Equilibrium by MOO
Conclusions
CO2 Emissions Targeting for Petroleum Refinery
Optimization
Mohmmad A. Al-Mayyahi, Andrew F.A. Hoadley and Gade Pandu
Rangaiah
Introduction
MOO-Pinch Analysis Framework to Target CO2 Emissions
Case Studies
Case Studies
Conclusions
Ecodesign of Chemical Processes with Multi-Objective Genetic
Algorithms
Catherine Azzaro-Pantel and Luc Pibouleau
Introduction
Numerical Tools
Williams–Otto Process (WOP) Optimization for Multiple Economic
and Environmental Objectives
Revisiting the HDA Process
Conclusions and Perspectives
Modeling and Multi-objective Optimization of a Chromatographic
System
Abhijit Tarafder
Introduction
Chromatography—Some Facts
Modeling Chromatographic Systems
Solving the Model Equations
Steps for Model Characterization
Description of the Optimization Routine—NSGA-II
Optimization of a Binary Separation in Chromatography
An Example Study
Conclusion
Estimation of Crystal Size Distribution: Image Thresholding
based on Multi-Objective Optimization
Karthik Raja Periasamy and S. Lakshminarayanan
Introduction
Methodology
Image Simulation
Image Preprocessing
Image Segmentation
Feature Extraction
Future Work
Conclusions
Multi-Objective Optimization of a Hybrid Steam
Stripper-Membrane Process for Continuous Bioethanol
Purification
Krishna Gudena, Gade Pandu Rangaiah and S
Lakshminarayanan
Introduction
Description and Design of a Hybrid Stripper-Membrane
System
Mathematical Formulation and Optimization
Results and Discussion
Conclusions
Exercises
Process Design for Economic, Environmental and Safety
Objectives with an Application to the Cumene Process
Shivom Sharma, Zi Chao Lim and Gade Pandu Rangaiah
Introduction
Review and Calculation of Safety Indices
Cumene Process, its Simulation and Costing
I2SI Calculation for Cumene Process
Optimization using EMOO Program
Optimization for Two Objectives
Optimization for EES Objectives
Conclusions
New PI Controller Tuning Methods Using Multi-Objective
Optimization
Allan Vandervoort, Jules Thibault and Yash Gupta
Introduction
PI Controller Model
Optimization Problem
Pareto Domain
Optimization Results
Controller Tuning
Application of the Tuning Methods
Conclusions
Index