Browsing by Author "Hsiao, CT"

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A four-role model of the automotive industry development in developing countries: a case in Taiwan
(2004-11-01)
Jan, TS
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Hsiao, CT
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管理科學系
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Department of Management Science
Developing countries often nurture the automotive industry as a path to technological and economic development. Initially, the government often sets up policies to protect the industry, but eventually the industry must face global competition. The process of industrial development for developing countries is complex and dynamic because many roles are involved in the development process. This study analyses the characteristics of the automobile industry in developing countries and the structure of the automotive industry system in Taiwan to explore the system behaviour using system dynamics methodology. The study proposes a four-role model to identify the structure where consumers play an important and subtle role in the development process. The implications for international leading automotive firms, the survival strategies of domestic companies, and the policies for developing country governments are also discussed.
Dynamic optimal ground water remediation including fixed and operation costs
(2002-09-01)
Chang, LC
;
Hsiao, CT
;
土木工程學系
;
Department of Civil Engineering
lit time-varying ground water remediation, the lack of an optimal control algorithm to simultaneously consider fixed costs and time-varying operating costs makes it nearly impossible to obtain an optimal solution. This study presents a novel algorithm that integrates a genetic algorithm (GA) and constrained differential dynamic programming (CDDP) to solve this time-varying ground water remediation problem. A GA can easily incorporate the fixed costs associated with the installation of wells. However, using a GA to solve for time-varying policies would dramatically increase the computational resources required. Therefore, the CDDP is used to handle the subproblems associated with time-varying operating costs. A hypothetical case study that incorporates fixed and time-varying operating costs is presented to demonstrate the effectiveness of the proposed algorithm. Simulation results indicate that the fixed costs can significantly influence the number and locations of wells, and a notable total cost savings can be realized by applying the novel algorithm herein.
Dynamic optimal groundwater management with inclusion of fixed costs
(2002-01-01)
Hsiao, CT
;
Chang, LC
;
土木工程學系
;
Department of Civil Engineering
Obtaining optimal solutions for groundwater resources planning problems, while simultaneously considering both fixed costs and time-varying pumping rates, is a challenging task. Application of conventional optimization algorithms such as linear and nonlinear programming is difficult due to the discontinuity of the fixed cost function in the objective function and the combinatorial nature of assigning discrete well locations. Use of conventional discrete algorithms such as integer programming or discrete dynamic programming is hampered by the large computational burden caused by varying pumping rates over time. A novel procedure that integrates a genetic algorithm (GA) with constrained differential dynamic programming (CDDP) calculates optimal solutions for a groundwater resources planning problem while simultaneously considering fixed costs and time-varying pumping rates. The GA deter-mines the number and locations of pumping wells with operating costs then evaluated using CDDP This study demonstrates that fixed costs associated with installing wells significantly impact the optimal number and locations of wells.
Optimal remediation design in groundwater systems by intelligent techniques
(2005)
Chu, HJ
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Hsiao, CT
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Chang, LC
;
土木工程學系
;
Department of Civil Engineering
This research develops an optimal planning model for pump-treat-inject based groundwater remediation systems. Optimizing the design of the pump-treat-inject system is a nonlinear, dynamic and discrete optimization problem. This study integrates the Genetic Algorithm (GA) and Differential Dynamic Programming (DDP) to solve this highly complex problem. The proposed model considers both the cost of installing wells (fixed cost) and the operating cost of pumping, injection and water treatment. Minimizing the total cost and meeting the water quality constraints, the model computes the optimal number and location of wells, as well as the associated optimal pumping and injection schemes. This work also investigates many factors that affect the optimal design of a remediation system, such as, various numerical cases revealing the time-varying pumping and injection rate, and the requirement to balance the total volume between pumping and injection that can significantly influence the optimal design.
Optimizing remediation of an unconfined aquifer using a hybrid algorithm
(2005-11-01)
Hsiao, CT
;
Chang, LC
;
土木工程學系
;
Department of Civil Engineering
We present a novel hybrid algorithm, integrating a genetic algorithm (GA) and constrained differential dynamic programming (CDDP), to achieve remediation planning for an unconfined aquifer. The objective function includes both fixed and dynamic operation costs. GA determines the primary structure of the proposed algorithm, and a chromosome therein implemented by a series of binary digits represents a potential network design. The time-varying optimal operation cost associated with the network design is computed by the CDDP, in which is embedded a numerical transport model. Several computational approaches, including a chromosome bookkeeping procedure, are implemented to alleviate computational loading. Additionally, case studies that involve fixed and time-varying operating costs for confined and unconfined aquifers, respectively, are discussed to elucidate the effectiveness of the proposed algorithm. Simulation results indicate that the fixed costs markedly affect the optimal design, including the number and locations of the wells. Furthermore, the solution obtained using the confined approximation for an unconfined aquifer may be infeasible, as determined by an unconfined simulation.