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|Title:||A PROGRESSIVE HEDGING BASED SAMPLE AVERAGE APPROXIMATION APPROACH TO STOCHASTIC MULTI-ECHELON MULTI-CHANNEL SUPPLY CHAIN NETWORK PLANNING||Authors:||SHI YURAN||Keywords:||Progressive Hedging, Sample Average Approximation, Stochastic Optimization, Supply Chain Planning, Network Optimization, Rolling Horizon Heuristic||Issue Date:||27-Dec-2017||Citation:||SHI YURAN (2017-12-27). A PROGRESSIVE HEDGING BASED SAMPLE AVERAGE APPROXIMATION APPROACH TO STOCHASTIC MULTI-ECHELON MULTI-CHANNEL SUPPLY CHAIN NETWORK PLANNING. ScholarBank@NUS Repository.||Abstract:||Effective supply chain planning in the high-tech consumer electronics industry is challenging due to the fast-moving market nature. This thesis studies a real supply chain network of a consumer electronics company. A stochastic multi-echelon multi-channel network model is formulated to solve the supply chain planning problem. The objective is to minimize overall operating cost throughout an extended planning horizon. Strategic decisions on long-term manufacturing capacity as well as operational plans on short-term production, inventory level and distribution options are determined at the same time. We present a progressive hedging based heuristic and a rolling horizon heuristic to accelerate the solving time of the large-scale problem. A nested sample average approximation method is used to examine the solution quality. A computational study of the real-world problem is presented to prove the solution quality and the efficiency of the proposed heuristics.||URI:||http://scholarbank.nus.edu.sg/handle/10635/146945|
|Appears in Collections:||Master's Theses (Open)|
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