Dynamic Pricing and Scheduling for the Coordination of a One-of-a-kind Production Supply Chain

dc.contributor.advisorTu, Yiliu
dc.contributor.authorZhang, Jian
dc.description.abstractIn this thesis work, we study the dynamic pricing strategy (DPS) for different cases and its influences on supply chain coordination. First, we study a DPS for a one-of-a-kind production (OKP) firm with two classes of orders (due-date guaranteed and due-date unguaranteed). We model the DPS using Bellman equation and compare it with a static pricing strategy (SPS). Second, we study the pricing problem for a third-party-logistics (3PL) provider that provides warehousing and less-than-truckload (LTL) transportation services. We develop a stochastic-nonlinear-programming (SNLP) model which computes the optimal freight rates for different delivery dates incorporating the 3PL provider's current holding cost and available transportation capacity. We develop an adjusted multinomial logit (MNL) function to predict customer choices so that our SNLP model can obtain near optimal freight rate settings. Finally, we study dynamic pricing based on a practical OKP firm which is currently employing a SPS. For the three cases, we show the increase of the price-setting firm's profit, customer and social welfare when DPS is employed through simulation, and consequently show the DPS's influence on the performance of the supply chain. We also develop a scheduling method for a manufacturer whose suppliers offer different delivery times at different prices. We abstract the problem to a one-machine scheduling problem which is featured by: (a) the release date of each job is compressible and stochastic, (b) each job has to be delivered before its due date (deadline) and (c) the manufacturer can expedite the production with costly overtime. The target is to minimize the total cost including the compressing cost and the overtime production cost. We coin a concept of a job's late-release-impact factor (LRIF) and we propose a LRIF based heuristic algorithm. Through the numerical test, we shows that the LRIF based algorithm can obtain a better schedule comparing to the ones that are commonly used in practice. By this thesis work, we are trying to integrate an OKP supply chain, which is critical to reduce the cost of OKP companies.en_US
dc.identifier.citationZhang, J. (2013). Dynamic Pricing and Scheduling for the Coordination of a One-of-a-kind Production Supply Chain (Doctoral thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca. doi:10.11575/PRISM/25759en_US
dc.publisher.facultyGraduate Studies
dc.publisher.institutionUniversity of Calgaryen
dc.rightsUniversity of Calgary graduate students retain copyright ownership and moral rights for their thesis. You may use this material in any way that is permitted by the Copyright Act or through licensing that has been assigned to the document. For uses that are not allowable under copyright legislation or licensing, you are required to seek permission.
dc.subjectOperations Research
dc.subject.classificationsupply chain managementen_US
dc.subject.classificationdecentralized coordinationen_US
dc.subject.classificationdynamic pricingen_US
dc.subject.classificationstochastic schedulingen_US
dc.titleDynamic Pricing and Scheduling for the Coordination of a One-of-a-kind Production Supply Chain
dc.typedoctoral thesis
thesis.degree.disciplineMechanical and Manufacturing Engineering
thesis.degree.grantorUniversity of Calgary
thesis.degree.nameDoctor of Philosophy (PhD)
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