Browsing by Author "Huang, Liang-Chuan"

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An integrated approach to the design and operation for spare parts logistic systems
(2011-04-01)
Wu, Muh-Cherng
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Hsu, Yang-Kang
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Huang, Liang-Chuan
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工業工程與管理學系
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Department of Industrial Engineering and Management
This paper attempts to solve a comprehensive design problem for a spare part logistic system. The design factors encompass logistic network design, part vendor selection, and transportation modes selection. Two approaches to solve the problem were proposed. In Approach 1, we simultaneously considered all the design factors and proposed two algorithms (SGA-1 and TGA-1). In Approach 2, the design problem was solved in two stages. Firstly, we aimed to find a near-optimal logistic network. Secondly, with the obtained logistic network, we proposed three algorithms (SGA-2. TGA-2, and NN-GA-Tabu) to find optimal combinations for part vendor and transportation modes selection. Numerical experiments indicate that Approach 2 outperforms Approach 1, and the NN-GA-Tabu outperforms all the other four algorithms. The proposed NN-GA-Tabu might also be a good solution architecture for solving other comprehensive space search problems. (C) 2010 Elsevier Ltd. All rights reserved.
Multiple lot-sizing decisions with an interrupted geometric yield and variable production time
(2009-10-01)
Hsu, Hsi-Mei
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Su, Tai-Sheng
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Wu, Muh-Cherng
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Huang, Liang-Chuan
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工業工程與管理學系
This study examines a multiple lot-sizing problem for a single-stage production system with an interrupted geometric distribution, which is distinguished in involving variable production lead-time. In a finite number of setups, this study determined the optimal lot-size for each period that minimizes total expected cost. The following cost items are considered in optimum lot-sizing decisions: setup cost, variable production cost, inventory holding cost, and shortage cost. A dynamic programming model is formulated in which the duration between current time and due date is a stage variable, and remaining demand and work-in-process status are state variables. This study then presents an algorithm for solving the dynamic programming problem. Additionally, this study examines how total expected costs of optimal lot-sizing decisions vary when parameters are changed. Numerical results show that the optimum lot-size as a function of demand is not always monotonic. (C) 2009 Elsevier Ltd. All rights reserved.