On the use of mathematical programs with complementarity constraints in combined topological and parametric design of biochemical enzyme networks

Tinghao Guo, James T. Allison

Research output: Contribution to journalArticlepeer-review

Abstract

A new method is presented for biochemical enzyme network design based on direct transcription and mathematical programs with complementarity constraints. Topology and continuous parameters are optimized simultaneously. The case study design objective is to optimize adaptability while maintaining sufficient sensitivity to ensure input change detection. A three-node problem is solved using both simultaneous and single-shooting approaches. The simultaneous approach enables solution of four-node problems; this is a new capability not available through existing approaches such as exhaustive enumeration, and is a step toward designing larger systems. A conventional nested solution strategy was also investigated for a four-node problem where an outer loop solves the discrete topology optimization problem, and an inner loop solves the continuous problem for each candidate topology. The simultaneous approach yields robust network topological designs that are superior to those identified through the single-shooting and nested strategies.

Original languageEnglish (US)
Pages (from-to)345-364
Number of pages20
JournalEngineering Optimization
Volume49
Issue number2
DOIs
StatePublished - Feb 1 2017

Keywords

  • direct transcription
  • enzyme network
  • nonlinear programming
  • synthetic biology
  • topology optimization

ASJC Scopus subject areas

  • Computer Science Applications
  • Control and Optimization
  • Management Science and Operations Research
  • Industrial and Manufacturing Engineering
  • Applied Mathematics

Fingerprint

Dive into the research topics of 'On the use of mathematical programs with complementarity constraints in combined topological and parametric design of biochemical enzyme networks'. Together they form a unique fingerprint.

Cite this