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Modeling supply network configuration problems with varying demand profiles

Conference Paper


Abstract


  • In this paper, we develop a novel multi-objective modeling approach to support supply network configuration decisions, while considering varying demand profiles. In so doing, we illustrate how such an approach could contribute to building supply network robustness and resilience. The proposed model entails two key objectives; minimizing lead time and cost across the supply network. The solution approach first employs a bidding mechanism to select a set of supply network entities that match with a given demand profile from a candidate pool of entities. It then applies the popular technique known as N on-dominated Sorting Genetic Algorithm-II to generate a set of Pareto-optimal solutions representing alternative supply network configurations. The proposed model is tested on a case study of a refrigerator supply network to draw delivery time and cost comparisons under static and dynamic demand profiles.

UOW Authors


  •   Dharmapriya, Subodha (external author)
  •   Kiridena, Senevi
  •   Shukla, Nagesh (external author)

Publication Date


  • 2018

Citation


  • Dharmapriya, S., Kiridena, S. & Shukla, N. (2018). Modeling supply network configuration problems with varying demand profiles. 2018 IEEE Technology and Engineering Management Conference, TEMSCON 2018 (pp. 1-6). United States: IEEE.

Scopus Eid


  • 2-s2.0-85056528565

Ro Metadata Url


  • http://ro.uow.edu.au/eispapers1/2359

Start Page


  • 1

End Page


  • 6

Place Of Publication


  • United States

Abstract


  • In this paper, we develop a novel multi-objective modeling approach to support supply network configuration decisions, while considering varying demand profiles. In so doing, we illustrate how such an approach could contribute to building supply network robustness and resilience. The proposed model entails two key objectives; minimizing lead time and cost across the supply network. The solution approach first employs a bidding mechanism to select a set of supply network entities that match with a given demand profile from a candidate pool of entities. It then applies the popular technique known as N on-dominated Sorting Genetic Algorithm-II to generate a set of Pareto-optimal solutions representing alternative supply network configurations. The proposed model is tested on a case study of a refrigerator supply network to draw delivery time and cost comparisons under static and dynamic demand profiles.

UOW Authors


  •   Dharmapriya, Subodha (external author)
  •   Kiridena, Senevi
  •   Shukla, Nagesh (external author)

Publication Date


  • 2018

Citation


  • Dharmapriya, S., Kiridena, S. & Shukla, N. (2018). Modeling supply network configuration problems with varying demand profiles. 2018 IEEE Technology and Engineering Management Conference, TEMSCON 2018 (pp. 1-6). United States: IEEE.

Scopus Eid


  • 2-s2.0-85056528565

Ro Metadata Url


  • http://ro.uow.edu.au/eispapers1/2359

Start Page


  • 1

End Page


  • 6

Place Of Publication


  • United States