{"id":{"repo_id":"missouri","oai_identifier":"oai:mospace.umsystem.edu:10355/46996"},"canonical_url":"https://search.dev.ndltd.org/etd/missouri/oai:mospace.umsystem.edu:10355/46996","repository":{"repo_id":"missouri","name":"University of Missouri","base_url":"https://mospace.umsystem.edu/oai/request"},"display":{"title":"Profit maximization of a kanban-based supply chain","abstract":"In this paper, we propose a stochastic method to model a multi-stage Kanban-based supply chain, constructed strictly under the JIT philosophy.This model decides the optimum number of Kanban with a trade-off between inventory cost and customer service level.After developing this model, we implement a Simulated Annealing (SA) technique to efficiently find the optimum allocation of this supply chain. Finally, we conduct sensitivity analysis, which not only proves the robustness of our model, but also provides us with a tool to make fact-based decisions in response to unexpected external changes. 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Finally, we conduct sensitivity analysis, which not only proves the robustness of our model, but also provides us with a tool to make fact-based decisions in response to unexpected external changes. This enables us to partially recover the profit when the changes are negative, or take a better advantage of changes when they are positive."]},{"key":"dc:source","label":"Dc Source","values":["Submitted to MOspace by University of Missouri--Columbia Graduate Studies."]},{"key":"dc:title","label":"Title","values":["Profit maximization of a kanban-based supply chain"]}]}],"canonical_facts":{"dc:contributor.advisor":["Noble, James S."],"dc:creator":["Chen, Peng"],"dc:date.accessioned":["2015-10-27T00:25:34Z"],"dc:date.available":["2015-10-27T00:25:34Z"],"dc:date.issued":["2015"],"dc:description.abstract":["In this paper, we propose a stochastic method to model a multi-stage Kanban-based supply chain, constructed strictly under the JIT philosophy.This model decides the optimum number of Kanban with a trade-off between inventory cost and customer service level.After developing this model, we implement a Simulated Annealing (SA) technique to efficiently find the optimum allocation of this supply chain. Finally, we conduct sensitivity analysis, which not only proves the robustness of our model, but also provides us with a tool to make fact-based decisions in response to unexpected external changes. This enables us to partially recover the profit when the changes are negative, or take a better advantage of changes when they are positive."],"dc:identifier.uri":["https://hdl.handle.net/10355/46996"],"dc:language":["English"],"dc:language.iso":["eng"],"dc:publisher":["University of Missouri--Columbia"],"dc:source":["Submitted to MOspace by University of Missouri--Columbia Graduate Studies."],"dc:title":["Profit maximization of a kanban-based supply chain"],"dc:type":["Thesis"],"thesis:degree_discipline":["Industrial and manufacturing systems engineering (MU)"],"thesis:degree_level":["Masters"],"thesis:degree_name":["M.S."],"thesis:institution_name":["University of Missouri--Columbia"]},"updated_at":"2026-07-24T03:07:46Z"}