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• W2519026265 abstract "As two major decisions in the supply chainmanagement, both resource management and sourcing strategies decide‘which product goes where at what amount and what time’, in orderto redeploy outbound/inbound resources to synchronize product flowand eventually fulfill customers’ requirements. Nowadays, thedifficulties in making such decisions are brought by many factorssuch as the emergence of globalization, the increasing variety ofproducts, and uncertainties in both demand and supply. In thisdissertation, quantitative methods are developed to efficiently useof all outbound/inbound resources for solving a multi-level andmulti-period supply chain system design and planning problem. Stochastic resource management model is afive-phase quantitative approach to decide facility location,capacity allocation, and production/shipping volume of the goodflow in a multi-stage manufacturing supply chain. In the proposedmodel, manufacturing system in each facility is configured (formingmanufacturing cells) at the same time when designing the supplychain network. In order to handle highly fluctuating demand, alayered mini-cellular system is developed, where product familieswith relatively stable demand are grouped and assigned to theirdedicated cells while shared and remainder cells handle the productfamilies with unstable demand. In addition to strategic andtactical decisions, phases IV and V also decide the productionplans and shipping plans to further study the operationaldecisions. Once the assignment of inboundresources has been determined by the resource management model, thelong-term sourcing model provides a dynamic framework to decide thequantity allocation of outbound resources. The goal of sourcingmodel is to capture supply uncertainties where supplier performancechanges along the time or based on purchasing decisions. Theproposed framework integrates simulation module and single-periodoptimization module. The former module simulates various changingpatterns of supplier performance. The latter one introduces fuzzyprogramming to identify the most ‘satisfied’ purchasingdecision with multiple objectives such as minimizing cost,improving quality and service level. Theproposed models are experimented with a global jewelrymanufacturing company with highly unstable demand. The results ofstochastic resource management model generally outperform those ofdeterministic model in terms of capacity requirements, servicelevels and costs. The impacts of parameters (minimal demandcoverage, reserved capacity, stage configuration) on bothstochastic model and deterministic model are also investigated toobtain an understanding of appropriate parameters. With regard tosourcing model, various single-period optimization models are firstanalyzed with different parameter settings, and an appropriateoptimization model is chosen. The changes of purchasing decisionsand supplier profiles along the simulation time are discussed indetail. The perfect alignment of experimentation…" @default.
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• W2519026265 date "2012-01-01" @default.
• W2519026265 modified "2023-09-23" @default.
• W2519026265 title "Resource Management and Sourcing Strategies in Supply Chain Coordination under an Uncertain Environment" @default.
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