z-logo
Premium
Optimal reactive operation of general topology supply chain and manufacturing networks under disruptions
Author(s) -
Ovalle Daniel,
Pulsipher Joshua L.,
Ye Yixin,
Harshbarger Kyle,
Bury Scott,
Laird Carl D.,
Grossmann Ignacio E.
Publication year - 2025
Publication title -
aiche journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.958
H-Index - 167
eISSN - 1547-5905
pISSN - 0001-1541
DOI - 10.1002/aic.18833
Subject(s) - supply chain , topology (electrical circuits) , chain (unit) , computer science , business , engineering , physics , electrical engineering , marketing , astronomy
Abstract Supply and manufacturing networks in the chemical industry involve diverse processing steps across different locations, rendering their operation vulnerable to disruptions from unplanned events. Optimal responses should consider factors such as product allocation, delayed shipments, and price renegotiation, among other factors. In such context, we propose a multiperiod mixed‐integer linear programming model that integrates production, scheduling, shipping, and order management to minimize the financial impact of such disruptions. The model accommodates arbitrary supply chain topologies and incorporates various disruption scenarios, offering adaptability to real‐world complexities. A case study from the chemical industry demonstrates the scalability of the model under finer time discretization and explores the influence of disruption types and order management costs on optimal schedules. This approach provides a tractable, adaptable framework for developing responsive operational plans in supply chain and manufacturing networks under uncertainty.

This content is not available in your region!

Continue researching here.

Having issues? You can contact us here
Empowering knowledge with every search

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom