In order to study the capacitated lot sizing problem for a supply chain of corporate multi-location factories to minimize the total costs of production, inventory and transportation under the system capacity restricti...In order to study the capacitated lot sizing problem for a supply chain of corporate multi-location factories to minimize the total costs of production, inventory and transportation under the system capacity restriction and product due date, while at the same time considering the menu distributed balance, the mathematical programming models are decomposed and reduced from the 3 levels into 2 levels according to the idea of just-in-time production. In order to overcome the premature convergence of ACA (ant colony algorithms), the idea of mute operation is adopted in genetic algorithms and a PACA (parallel ant colony algorithms) is proposed for supply chain optimization. Finally, an illustrative example is given, and a comparison is made with standard BAB (Branch and Bound) and PACA approach. The result shows that the latter is more effective and promising.展开更多
Clothing manufacturers＇ direct investment and joint ventures in developing regions have seen to grow rapidly in the past few decades. Non-optimized selection can contribute to adverse effects affecting the performanc...Clothing manufacturers＇ direct investment and joint ventures in developing regions have seen to grow rapidly in the past few decades. Non-optimized selection can contribute to adverse effects affecting the performance of the plants on aspects of productivity, manufacturing and logistics cost. Selection of proper plant location is thus crucial. The conventional approaches to sites location are based on the factors and their weights. However, determining the weight of each factor is very difficult and time consuming. While the situation is changed, all the work must be redone again. This study aims to develop a decision-making system on clothing plant location for Hoog Kong clothing manufacturer. The proposed system utilizes artificial neural network to study the relationship between the factors and the suitability index of candidate sites. Firstly, the factors are stratified using the fuzzy analytical hierarchy process （FAHP） by review the related references and interviewing the experts. Secondly, the corresponding data are collected from the experts by questionnaire and the related government publication. Finally, the feedforward neural network with error backpropagation（EBP） learning algorithm is trained and applied to make decision. The results show that the proposed system performs well and has the characteristic of adaptability and plasticity.展开更多
文摘In order to study the capacitated lot sizing problem for a supply chain of corporate multi-location factories to minimize the total costs of production, inventory and transportation under the system capacity restriction and product due date, while at the same time considering the menu distributed balance, the mathematical programming models are decomposed and reduced from the 3 levels into 2 levels according to the idea of just-in-time production. In order to overcome the premature convergence of ACA (ant colony algorithms), the idea of mute operation is adopted in genetic algorithms and a PACA (parallel ant colony algorithms) is proposed for supply chain optimization. Finally, an illustrative example is given, and a comparison is made with standard BAB (Branch and Bound) and PACA approach. The result shows that the latter is more effective and promising.
文摘Clothing manufacturers＇ direct investment and joint ventures in developing regions have seen to grow rapidly in the past few decades. Non-optimized selection can contribute to adverse effects affecting the performance of the plants on aspects of productivity, manufacturing and logistics cost. Selection of proper plant location is thus crucial. The conventional approaches to sites location are based on the factors and their weights. However, determining the weight of each factor is very difficult and time consuming. While the situation is changed, all the work must be redone again. This study aims to develop a decision-making system on clothing plant location for Hoog Kong clothing manufacturer. The proposed system utilizes artificial neural network to study the relationship between the factors and the suitability index of candidate sites. Firstly, the factors are stratified using the fuzzy analytical hierarchy process （FAHP） by review the related references and interviewing the experts. Secondly, the corresponding data are collected from the experts by questionnaire and the related government publication. Finally, the feedforward neural network with error backpropagation（EBP） learning algorithm is trained and applied to make decision. The results show that the proposed system performs well and has the characteristic of adaptability and plasticity.
