List of Contributors xiii Preface xvii 1 An Introduction to Bilevel Optimization and Its Application to Sustainable Systems Engineering 1 Rishabh Gupta, Jnana S. Jagana, Tushar Rathi, and Qi Zhang 1.1 Introduction 1 1.2 Fundamentals of Bilevel Optimization 2 1.2.1 Mathematical Formulation 2 1.2.1.

1 Optimistic Versus Pessimistic Bilevel Optimization 3 1.2.1.2 High-Point Relaxation 4 1.2.1.3 When to Not Use Bilevel Optimization 4 1.2.

2 KKT Reformulation 6 1.2.2.1 "Naive" KKT Reformulation 6 1.2.2.2 Mixed-Integer Programming Reformulation 6 1.2.

2.3 Branching on Complementarity Constraints 7 1.2.2.4 Penalty-Based Reformulation 8 1.2.3 Value-Function Reformulation 8 1.2.

3.1 Reformulation Using the Optimal-Value Function 9 1.2.3.2 Kth-Best Algorithm 9 1.2.3.3 Cutting-Plane Approach 11 1.

3 Some Applications in Sustainable Systems Engineering 12 1.4 Bilevel Optimization for Machine Learning 14 1.4.1 Data-Driven Inverse Optimization 14 1.4.2 Hyperparameter Tuning 17 1.4.3 Algorithms for Large-Scale Bilevel Optimization 20 1.

4.3.1 Implicit Estimation 21 1.4.3.2 Explicit Estimation 22 1.5 Robust Optimization 25 1.5.

1 Mathematical Formulation 26 1.5.1.1 Reformulation 27 1.5.1.2 Cutting-Plane Approach 28 1.5.

2 Adjustable Robust Optimization 28 1.5.3 Applications 29 1.5.4 Case Study 30 1.6 Conclusions 33 References 34 2 Exploiting the Multiscale Structure of Sustainable Engineering Problems via Network-Based Decomposition 43 Ilias Mitrai and Prodromos Daoutidis 2.1 Introduction 43 2.2 Learning the Structure of Optimization Problems 45 2.

2.1 Optimization Problems as Graphs 45 2.2.2 Learning the Structure via Stochastic Blockmodeling 46 2.3 Network-Based Decomposition of Optimization Problems 48 2.3.1 Benders Decomposition Based on the Variable Graph 48 2.3.

2 Lagrangean Decomposition Based on the Structure of the Constraint Graph 50 2.4 Case Study: Transition to Green Ammonia Supply Chain Networks 52 2.4.1 Two-Stage Stochastic Programming Problem Formulation 52 2.4.2 Structure of the Optimization Problem 53 2.4.3 Numerical Results 57 2.

5 Conclusions 57 References 58 3 Multi-Objective Bayesian Optimization for Networked Black-Box Systems: A Path to Greener Profits and Smarter Designs 63 Akshay Kudva, Wei-Ting Tang, and Joel A. Paulson 3.1 Introduction 63 3.2 Problem Formulation 66 3.3 Multi-Objective Bayesian Optimization Over Network Systems 68 3.3.1 Statistical Surrogate Model 69 3.3.

2 Multi-Objective Thompson Sampling for Function Networks 70 3.3.3 Practical Considerations in MOBONS 71 3.3.3.1 GP Kernel Selection and Tuning 71 3.3.3.

2 Thompson Sampling 73 3.3.3.3 Approximating the Pareto Optimal Set 73 3.3.3.4 Selection Function 74 3.3.

4 Handling Parallel Evaluations and Constrained Problems 74 3.4 Case Studies 75 3.4.1 Baseline Methods for Comparison 75 3.4.2 Synthetic Test Problem: ZDT4 Benchmark 76 3.4.3 Design of Sustainable Bioethanol Process 79 3.

4.3.1 Process Description and Implementation 79 3.4.3.2 Problem Formulation and Function Network Representation 79 3.4.3.

3 Optimization Performance and Hypervolume Analysis 81 3.4.3.4 Local Sensitivity Analysis 82 3.5 Conclusion 84 References 85 4 A Tutorial on Multi-time Scale Optimization Models and Algorithms 91 Asha Ramanujam and Can li 4.1 Introduction 91 4.2 Multi-time Scale Optimization Models 92 4.3 Value of the Multi-scale Model (VMM) 94 4.

4 Algorithms to Solve Multi-time Scale Optimization Models 96 4.4.1 Full-Space Methods 96 4.4.2 Decomposition Algorithms 97 4.4.2.1 Bi-level Decomposition 98 4.

4.2.2 Dual-Based Decomposition Algorithms 100 4.4.2.3 Limitations of Decomposition Algorithms 113 4.4.3 Metaheuristic Algorithms 113 4.

4.4 Matheuristic Algorithms 114 4.4.5 Data-Driven Methods 115 4.4.6 Pamso 117 4.5 Illustrative Example 119 4.5.

1 Problem Statement 119 4.5.2 Integrated Model 119 4.5.2.1 Indices and Sets 119 4.5.2.

2 Variables 119 4.5.2.3 Parameters 120 4.5.2.4 Constraints 120 4.5.

2.5 Objective 120 4.5.2.6 Optimization Model 120 4.5.3 Solving the Problem 121 4.5.

3.1 Using Full-Space Method 121 4.5.3.2 Using Benders Decomposition 121 4.5.3.3 Using Lagrangian Decomposition 122 4.

5.3.4 Using Dantzig-Wolfe Decomposition 124 4.5.3.5 Using PAMSO 126 4.5.4 Vmm 128 4.

6 Conclusion 129 References 129 5 Many Objective Optimization Tools for Sustainable Decision-Making 135 Andrew Allman and Hongxuan Wang 5.1 Introduction 135 5.2 Sustainability Objectives 136 5.3 MOP Solution Methods 138 5.4 Objective Dimensionality Reduction for MaOPs 141 5.5 Case Study: Cost Versus Emissions-Driven Demand Response 144 5.6 Case Study: Analysis of Planetary Boundary Objectives 147 5.7 Conclusion and Future Perspectives 150 References 151 6 Optimization Models and Algorithms for Design and Planning of Sustainable Processes and Energy Systems 155 Seolhee Cho and Ignacio E.

Grossmann 6.1 Introduction 155 6.2 Optimization Models 156 6.2.1 Continuous Optimization 157 6.2.2 Discrete Optimization 157 6.2.

3 Logic-Based Optimization 158 6.2.4 Optimization Under Uncertainty 159 6.3 Solution Strategies 160 6.3.1 Benders Decomposition 160 6.3.2 Lagrangean Decomposition 161 6.

3.3 Bilevel Decomposition 162 6.4 Algebraic Modeling Languages 162 6.5 Applications in Sustainable Process and Energy Systems 164 6.5.1 Hydrogen 164 6.5.2 Biomass 165 6.

5.3 Methanol 166 6.5.4 Power Systems 167 6.6 Conclusions 169 References 169 7 Multiscale Modeling and Optimization of Carbon Capture Processes 179 Kyeongjun Seo, Mark A. Stadtherr, and Michael Baldea 7.1 Introduction 179 7.2 Modeling of Carbon Capture Processes 180 7.

2.1 Process Structure and Operation 180 7.2.2 Mathematical Modeling 183 7.2.3 Multiscale Optimization 185 7.3 Multiscale Modeling and Optimization Results 187 7.4 Conclusions 193 Acknowledgments 194 Disclaimer 194 References 195 8 Integrated Design and Operability Optimization of Sustainable Process Intensification Systems 199 Yuhe Tian, Rahul Bindlish, and Efstratios N.

Pistikopoulos 8.1 Introduction 199 8.2 Methodology Framework 202 8.2.1 Prelude: Phenomena-Based Process Synthesis 202 8.2.2 Generalized Modular Representation Framework 203 8.2.

3 Integrated Synthesis and Operability Optimization 205 8.2.3.1 Safety Considerations via Risk Analysis 205 8.2.3.2 Design Under Uncertainty via Flexibility Analysis 208 8.3 Case Studies 210 8.

3.1 MMA Purification 210 8.3.1.1 Process Description 210 8.3.1.2 GMF Simulation of Base Case Design 211 8.

3.1.3 GMF Synthesis for Grassroots Design 212 8.3.2 MTBE Production 214 8.3.2.1 Process Description 214 8.

3.2.2 Integrated GMF Synthesis and Operability Optimization 215 8.4 Concluding Remarks 218 Acknowledgment 218 References 218 9 Circular Economy Assessment Tools for Process Systems 223 Paola Munoz-Briones, Kenneth Martinez, Javiera Vergara-Zambrano, and Styliani Avraamidou 9.1 Introduction 223 9.2 Circular Economy Assessment in the Food Sector 226 9.2.1 Example: CE Assessment for Food Packaging Waste Management Technologies 230 9.

3 Circular Economy Assessment in the Chemical Industry 232 9.3.1 Example: Circular Economy Assessment of Viable for Fuels for Mobility 235 9.4 Circular Economy Metrics for Energy Systems 237 References 240 10 Decarbonization of Steam Cracking for Clean Olefins Production: Optimal Microgrid Scheduling 251 Saba Ghasemi Naraghi, Tylee Kareck, Lingyun Xiao, Richard Reed, Paritosh Ramanan, and Zheyu Jiang 10.1 Introduction 251 10.2 Dynamic Optimization of Steam Cracking Process 254 10.3 Scenario-Based Optimal Microgrid Scheduling Problem 258 10.4 Illustrative Case Studies 265 10.

4.1 Problem Setting 265 10.4.2 Grid-Connected Mode 267 10.4.3 Islanded Mode 272 10.5 Conclusion 275 Acknowledgments 275 References 276 11 Multiscale Strategies for the Use of Chemicals as Energy Storage Systems 279 Diego Santamaría, Antonio Sánchez, and Mariano Martín 11.1 Introduction 279 11.

2 Methodology 279 11.2.1 Process Design 280 11.2.2 Process Scale Up/Down 282 11.2.3 Enterprise-Wide Level 283 11.3 Cases of Study 285 11.

3.1 Hydrogen 285 11.3.2 Methane 291 11.3.3 Methanol 295 11.3.4 Ammonia 298 11.

4 Conclusions 304 Acknowledgment 304 References 304 12 Repurposing a Conventional Oil Refinery for Biomass Processing to Aviation Fuel: Process Design and Techno-Environmental Evaluation for a Real Operating Plant 317 Valeria González, Alejandro Pedezert, Soledad Gutiérrez, Roberto Kreimerman, Lucia Pittaluga, and Ana I. Torres 12.1 Introduction 317 12.2 Overview of Feed Options, Processing P.