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Chapter 12 Supply chain optimization for chemical and biochemical processes

  • Yulissa Mercedes Espinoza-Vázquez , Nereyda Vanessa Hernández-Camacho , Jahaziel Alberto Sánchez-Gómez , José Ezequiel Santibañez-Aguilar and Fernando Israel Gómez-Castro
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Optimization in Chemical Engineering
This chapter is in the book Optimization in Chemical Engineering

Abstract

The optimal design of conversion processes is highly relevant for the chemical and biochemical industries, besides the determination of optimal operation policies. However, the selection of an adequate strategy to distribute the raw materials to the facilities and the products to the markets, i.e., the supply chain, is indispensable to ensure the economic feasibility of the macroscopic production scheme. In this chapter, the importance of the optimization of supply chains for chemical and biochemical processes is described. The use of logic-based and mixed-integer models to represent and optimize supply chains is discussed. Guidelines to properly select the objective function are presented, grouping the objectives as economic, environmental, and social functions. Finally, an example of the modeling and optimization of a supply chain for the conversion of glycerol into valuable derivatives is discussed

Abstract

The optimal design of conversion processes is highly relevant for the chemical and biochemical industries, besides the determination of optimal operation policies. However, the selection of an adequate strategy to distribute the raw materials to the facilities and the products to the markets, i.e., the supply chain, is indispensable to ensure the economic feasibility of the macroscopic production scheme. In this chapter, the importance of the optimization of supply chains for chemical and biochemical processes is described. The use of logic-based and mixed-integer models to represent and optimize supply chains is discussed. Guidelines to properly select the objective function are presented, grouping the objectives as economic, environmental, and social functions. Finally, an example of the modeling and optimization of a supply chain for the conversion of glycerol into valuable derivatives is discussed

Chapters in this book

  1. Frontmatter I
  2. Contents V
  3. List of contributing authors VII
  4. Chapter 1 Optimization and its importance for chemical engineers: challenges, opportunities, and innovations 1
  5. Chapter 2 Deterministic optimization of distillation processes 25
  6. Chapter 3 Optimal design of process energy systems integrating sustainable considerations 79
  7. Chapter 4 Metaheuristics for the optimization of chemical processes 113
  8. Chapter 5 Surrogate-based optimization techniques for process systems engineering 159
  9. Chapter 6 Data-driven techniques for optimal and sustainable process integration of chemical and manufacturing systems 215
  10. Chapter 7 Applications of Bayesian optimization in chemical engineering 255
  11. Chapter 8 Sensitivity assessment of multi-criteria decision-making methods in chemical engineering optimization applications 283
  12. Chapter 9 Hybrid optimization methodologies for the design of chemical processes 305
  13. Chapter 10 Optimization under uncertainty in process systems engineering 343
  14. Chapter 11 Optimal control of batch processes in the continuous time domain 379
  15. Chapter 12 Supply chain optimization for chemical and biochemical processes 401
  16. Chapter 13 Future insights for optimization in chemical engineering 425
  17. Index 445
https://doi.org/10.1515/9783111383439-012

Chapters in this book

  1. Frontmatter I
  2. Contents V
  3. List of contributing authors VII
  4. Chapter 1 Optimization and its importance for chemical engineers: challenges, opportunities, and innovations 1
  5. Chapter 2 Deterministic optimization of distillation processes 25
  6. Chapter 3 Optimal design of process energy systems integrating sustainable considerations 79
  7. Chapter 4 Metaheuristics for the optimization of chemical processes 113
  8. Chapter 5 Surrogate-based optimization techniques for process systems engineering 159
  9. Chapter 6 Data-driven techniques for optimal and sustainable process integration of chemical and manufacturing systems 215
  10. Chapter 7 Applications of Bayesian optimization in chemical engineering 255
  11. Chapter 8 Sensitivity assessment of multi-criteria decision-making methods in chemical engineering optimization applications 283
  12. Chapter 9 Hybrid optimization methodologies for the design of chemical processes 305
  13. Chapter 10 Optimization under uncertainty in process systems engineering 343
  14. Chapter 11 Optimal control of batch processes in the continuous time domain 379
  15. Chapter 12 Supply chain optimization for chemical and biochemical processes 401
  16. Chapter 13 Future insights for optimization in chemical engineering 425
  17. Index 445
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