Fair profit allocation in supply chain optimization with transfer price and revenue sharing: MINLP model and algorithm for cellulosic biofuel supply chains

Dajun Yue, Fengqi You*

*Corresponding author for this work

Research output: Contribution to journalArticle

47 Scopus citations

Abstract

A mixed-integer nonlinear programming (MINLP) formulation to simultaneously optimize operational decisions as well as profit allocation mechanisms in supply chain optimization, namely material transfer prices and revenue share policies among the supply chain participants is proposed. The case of cellulosic bioethanol supply chains is specifically considered and the game-theory Nash bargaining solution approach is employed to achieve fair allocation of profit among the collection facilities, biorefineries, and distribution centers. The structural advantages of certain supply chain participants can be taken into account by specifying different values of the negotiation-power indicators in the generalized Nash-type objective function. A solution strategy based on a logarithm transformation and a branch-and-refine algorithm for efficient global optimization of the resulting nonconvex MINLP problem is proposed. To demonstrate the application of the proposed framework, an illustrative example and a state-wide county-level case study on the optimization of a potential cellulosic bioethanol supply chain in Illinois are presented.

Original languageEnglish (US)
Pages (from-to)3211-3229
Number of pages19
JournalAICHE Journal
Volume60
Issue number9
DOIs
StatePublished - Jan 1 2014

Keywords

  • Cellulosic bioethanol
  • Game theory
  • Global optimization
  • Revenue sharing policy
  • Transfer price

ASJC Scopus subject areas

  • Biotechnology
  • Environmental Engineering
  • Chemical Engineering(all)

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