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Multiagent Optimization Approach to Supply Network Configuration Problems With Varied Product-Market Profiles

Journal Article


Abstract


  • This article demonstrates the application of a novel multiagent modeling approach to support supply network configuration (SNC) decisions toward addressing several challenges reported in the literature. These challenges include: enhancing supply network (SN)-level performance in alignment with the goals of individual SN entities; addressing the issue of limited information sharing between SN entities; and sustaining competitiveness of SNs in dynamic business environments. To this end, a multistage, multiechelon SN consisting of geographically dispersed SN entities catering to distinct product-market profiles was modeled. In modeling the SNC decision problem, two types of agents, each having distinct attributes and functions, were used. The modeling approach incorporated a reverse-auctioning process to simulate the behavior of SN entities with differing individual goals collectively contributing to enhance SN-level performance, by means of setting reserve values generated through the application of a genetic algorithm. A set of Pareto-optimal SNCs catering to distinct product-market profiles was generated using Nondominated Sorting Genetic Algorithm II. Further evaluation of these SNCs against additional criteria, using a rule-based approach, allowed the selection of the most appropriate SNC to meet a broader set of conditions. The model was tested using a refrigerator SN case study drawn from the literature. The results reveal that a number of SNC decisions can be supported by the proposed model, in particular, identifying and evaluating robust SNs to suit varied product-market profiles, enhancing SC capabilities to withstand disruptions and developing contingencies to recover from disruptions.

Publication Date


  • 2022

Citation


  • Dharmapriya, S., Kiridena, S., & Shukla, N. (2022). Multiagent Optimization Approach to Supply Network Configuration Problems With Varied Product-Market Profiles. IEEE Transactions on Engineering Management, 69(6), 2707-2722. doi:10.1109/TEM.2019.2950694

Scopus Eid


  • 2-s2.0-85076272708

Start Page


  • 2707

End Page


  • 2722

Volume


  • 69

Issue


  • 6

Place Of Publication


Abstract


  • This article demonstrates the application of a novel multiagent modeling approach to support supply network configuration (SNC) decisions toward addressing several challenges reported in the literature. These challenges include: enhancing supply network (SN)-level performance in alignment with the goals of individual SN entities; addressing the issue of limited information sharing between SN entities; and sustaining competitiveness of SNs in dynamic business environments. To this end, a multistage, multiechelon SN consisting of geographically dispersed SN entities catering to distinct product-market profiles was modeled. In modeling the SNC decision problem, two types of agents, each having distinct attributes and functions, were used. The modeling approach incorporated a reverse-auctioning process to simulate the behavior of SN entities with differing individual goals collectively contributing to enhance SN-level performance, by means of setting reserve values generated through the application of a genetic algorithm. A set of Pareto-optimal SNCs catering to distinct product-market profiles was generated using Nondominated Sorting Genetic Algorithm II. Further evaluation of these SNCs against additional criteria, using a rule-based approach, allowed the selection of the most appropriate SNC to meet a broader set of conditions. The model was tested using a refrigerator SN case study drawn from the literature. The results reveal that a number of SNC decisions can be supported by the proposed model, in particular, identifying and evaluating robust SNs to suit varied product-market profiles, enhancing SC capabilities to withstand disruptions and developing contingencies to recover from disruptions.

Publication Date


  • 2022

Citation


  • Dharmapriya, S., Kiridena, S., & Shukla, N. (2022). Multiagent Optimization Approach to Supply Network Configuration Problems With Varied Product-Market Profiles. IEEE Transactions on Engineering Management, 69(6), 2707-2722. doi:10.1109/TEM.2019.2950694

Scopus Eid


  • 2-s2.0-85076272708

Start Page


  • 2707

End Page


  • 2722

Volume


  • 69

Issue


  • 6

Place Of Publication