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A framework and algorithm for fair demand and capacity sharing in collaborative networks

  • State University of New York Binghamton University
  • Hongik University

Research output: Contribution to journalReview articlepeer-review

14 Scopus citations

Abstract

This paper presents a framework for balancing fairness and efficiency in the collaborative networks (CNs) of enterprises. In any CN, the collaboration process often leads to a dilemma: the need to choose between fairness and efficiency. The objective of this research is to propose an algorithm that attempts to increase optimal weights of fairness while maintaining efficiency. In this research, two concepts are utilized to distinguish the balance between fairness and efficiency in CNs: 1) the generalized α-fair concept; and 2) Jain's fairness index. The performance of the proposed algorithm has been tested with conceptual heterogeneous and homogeneous CNs (HeCNs and HoCNs, respectively) based on the enterprise capacity. The experimental results indicate that a balance between efficiency and fairness in CNs is possible while forming a network and obtaining mutual benefits fairly among the enterprises. In addition, the proposed algorithm can minimize the deviation between most and least beneficial enterprises in CN in terms of total profit, lost sale cost, and inventory cost.

Original languageEnglish
Pages (from-to)137-147
Number of pages11
JournalInternational Journal of Production Economics
Volume193
DOIs
StatePublished - Nov 2017

Keywords

  • Collaborative network
  • Distributed decision making
  • Fairness
  • Network efficiency
  • Sharing protocols

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