Modeling methods and a branch and cut algorithm for pharmaceutical clinical trial planning using stochastic programming

Matthew Colvin, Christos T. Maravelias

Research output: Contribution to journalArticlepeer-review

63 Scopus citations

Abstract

We discuss methods for the solution of a multi-stage stochastic programming formulation for the resource-constrained scheduling of clinical trials in the pharmaceutical research and development pipeline. First, we present a number of theoretical properties to reduce the size and improve the tightness of the formulation, focusing primarily on non-anticipativity constraints. Second, we develop a novel branch and cut algorithm where necessary non-anticipativity constraints that are unlikely to be active are removed from the initial formulation and only added if they are violated within the search tree. We improve the performance of our algorithm by combining different node selection strategies and exploring different approaches to constraint violation checking.

Original languageEnglish (US)
Pages (from-to)205-215
Number of pages11
JournalEuropean Journal of Operational Research
Volume203
Issue number1
DOIs
StatePublished - May 16 2010
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Computer Science(all)
  • Modeling and Simulation
  • Management Science and Operations Research
  • Information Systems and Management

Keywords

  • Branch and cut
  • Integer programming
  • Pharmaceutical research and development
  • Project scheduling
  • Stochastic programming

Fingerprint

Dive into the research topics of 'Modeling methods and a branch and cut algorithm for pharmaceutical clinical trial planning using stochastic programming'. Together they form a unique fingerprint.

Cite this