LAUSR.org creates dashboard-style pages of related content for over 1.5 million academic articles. Sign Up to like articles & get recommendations!

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

Photo by mariusoprea from unsplash

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… Click to show full 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.

Keywords: capacity; framework algorithm; fairness efficiency; collaborative networks; efficiency

Journal Title: International Journal of Production Economics
Year Published: 2017

Link to full text (if available)


Share on Social Media:                               Sign Up to like & get
recommendations!

Related content

More Information              News              Social Media              Video              Recommended



                Click one of the above tabs to view related content.