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    31 August 2012, Volume 15 Issue 4 Previous Issue    Next Issue
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    articles
    Forecast of Railway Container Freight Volume by Using a Combinatorial Model
    Lin Bing-kun, Cheng Wen-ming, Yu Lan-feng
    2012, 15 (4):  1-6. 
    Abstract ( 2621 )   Save
    The forecast of railway container freight volume has significant effect on the operation and development of the railway. The existing forecast models can forecast a single index only, which is not accurate enough. To overcome this disadvantage, the combinatorial forecast model is adopted to forecast railway container freight volume. Based on the historical data, individual index forecast models are derived by using linear polynomial and grey models, respectively. Then, the individual index forecast models are combined by using radial basis function (RBF) neural network. Analysis shows that, in comparison with two single index forecast models, the combinatorial forecast model can improve the forecast result of relative error by 3.19% and 12.76%, respectively. Finally, the combinatorial forecast result is analyzed and modified by Markov chain model.
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    Modeling and Optimization of Multimodal Transportation  with Fuzzy Time Window
    Xiong Gui-wu1,2
    2012, 15 (4):  7-11. 
    Abstract ( 2562 )   Save
    The problem of modeling and optimization of multimodal transportation with fuzzy time window is discussed in this paper. Based on a network description for this problem, an optimization model is presented for it. After analyzing the characteristics of the model, a hybrid Taguchi genetic algorithm is then proposed to solve the problem. It optimizes the transportation routes and the combination of means of transportation. An example with five orders that have different fuzzy time windows is use to show the effectiveness of the proposed method. Numerical results show that it is efficient and satisfied result can be obtained.
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    Method of Monitoring Abnormality under Integrated SPC/EPC Based on Neural Network Techniques
    Wang Xiu-hong
    2012, 15 (4):  12-16. 
    Abstract ( 2399 )   Save
    It is known that, under the integrated scheme of  statistical process control(SPC) and engineering process control(EPC), the SPCs capability of monitoring the feedback-controlled process is low.To resolve this problem, neural network techniques are introduced into the integrated SPC/EPC method. Based on structural analysis and parameter setting, a three-layer neural network model is presented. For model training, the input data include process inputs, process outputs, and their covariance, and the output dada are whether an abnormality occurs. A number of tests are done to compare with Shewhart chart and CUSUM chart methods. Results show that the proposed model outperforms traditional SPC methods. It can accurately monitor a process for step disturbance with change over 2 and process drift with range over 2, and average run length(ARL) value equal to 1. While the traditional SPC methods can correctly monitor a process (monitoring rate > 90%) only for step disturbance with change over 5 and process drift with range over 2, and ARL value greater than 2.
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    Quality Prediction Model by Using PSO-BP Neural Network
    Xu Lan1,2, Fang Zhi-geng1, Liu Si-feng1
    2012, 15 (4):  17-20. 
    Abstract ( 2577 )   Save
    For quality assurance, it is very important to make effective quality prediction in the stage of product design and parameter optimization. To do so, by using PSO (particle swarm optimization) and BP (back propagation) neural network, a quality prediction model is established. It is an optimization problem with grey incidence degree between the networks output and input as objective. PSO algorithm is used to optimize the BP neural networks weight coefficient and threshold value. Then, a PSO-GRG (grey relational grade) algorithm is proposed to solve the problem. This algorithm overcomes general BP algorithms shortcomings of slow convergence and local optimum solution. A case problem of injection molding is used to verify the proposed method. Simulation results show that the prediction errors are significantly reduced with the number of iterations being reduced by 87.5%.
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    Performance Evaluation for a Multi-Shuttle Automated Storage and Retrieval System
    Yang Peng, Miao Li-xin
    2012, 15 (4):  21-27. 
    Abstract ( 2407 )   Save
    The automated storage and retrieval system (AS/RS) with multiple shuttles are addressed in this paper. It is assumed that the system operates under the first-come-first-served and nearest neighbor scheduling rules. According to the operational characteristics of the system, analytical models for expected travel time estimation are derived. These models are applicable for evaluating throughput of multi-shuttle AS/RS for circumstance with different number of shuttles and different types of shelves. The proposed method is validated by the Monte Carlo simulation. Results show that the proposed models are effective and accurate for evaluating the throughput of multi-shuttle AS/RS.
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    Stackelberg Game Model for Two-Level Supply Chain with Fairness Preference
    Wang Yong, Zhu Long-tao
    2012, 15 (4):  28-34. 
    Abstract ( 2605 )   Save
    Fairness preference has significant effect on the operation in a supply chain. With fairness preference taken into account in this paper, a Stackelberg game model is developed for a two-level supply chain. Further, utility functions are established by introducing reference point effect. Then the effect of fairness on the supply chain partners strategies is analyzed for three cases: the retailer concerns about fairness only, the supplier concerns about fairness only, and both partners concern about fairness. Results show that fairness preference changes the revenue sharing rate and the retailers effort level. Also, fairness preference influences partners utility values in a supply chain, and the greater the fairness degree is, the more obvious the influence is.
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    MFA-Based Resource Cycling Efficiency Analysis for a Closed-Loop Supply Chain System
    Su Li-xia1, Wang Zhao-hua1, Yang Zhong-min1,2, Zhang Bin1
    2012, 15 (4):  35-40. 
    Abstract ( 2388 )   Save
    The recycling problem for electronic products under a closed-loop supply chain environment is addressed in this paper. The cycling efficiency is analyzed by using material flow analysis (MFA). Then, a mathematical model is developed to optimize the recycling efficiency for such a supply chain. By this model, the circulation index and path length are measured by the amount of the substance at each node in the system, which reflects the material utilization and recycling efficiency of the whole system. Thus, it reveals how one can increase the resource recycling efficiency. It shows that the circulation index can be improved by green manufacturing and green design. This is a significant finding in this field. Finally, the model is tested and analyzed through an e-waste recycling numerical example.
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    A Research on Coordination of VMI&TPL Supply Chain under Centralized Control
    Liu Yang, Zhao Dao-zhi, He Long-fei
    2012, 15 (4):  41-46. 
    Abstract ( 2376 )   Save
    The coordination problem of a supply chain under vendor managed inventory (VMI) mode with third party logistics (TPL) is studied in this paper. In the supply chain, the demands are subject to random disturbance. It is assume that the supply chain is coordinated by revenue sharing (RS) contract and it is operated under centralized control mode. Consider that the basic RS contract is no longer effective, an RS contract with the stock risk shared by retailer, supplier, and TPL is proposed to coordinate the supply chain. This contract is further extended to the RS contract combined with risk-sharing under Asymmetric Nash Negotiation. With these contracts, analysis is carried out. Results show that while the RS contract with risk-sharing can maximize the expected revenue of whole supply chain, the one with risk-sharing under Asymmetric Nash Negotiation can coordinate the supply chain well and at the same time the Pareto improvement for every member's expected revenue can be achieved.
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    An Extended Newsvendor Model with Service Level Constraint and Capacity Constraint
    Xie Yong, Xiang Li, Wang Hong-wei, Chen Shuang
    2012, 15 (4):  47-52. 
    Abstract ( 2654 )   Save
    Extended newsvendor models are considered in this paper for two cases: one with service level constraint and the other with capacity constraint. We first develop the two models with service level constraint and capacity constraint, respectively. Then, optimal order quantity for these two cases is derived and the properties of optimal solutions are analyzed. Based on the analysis results, an extended newsvendor model with both service level and capacity constraints are presented. Then, effect of service level and capacity constraints on the optimal order quantity and the expected profit of the newsvendor is explored. A numerical study is presented to illustrate and validate the proposed method.
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    Principal-Agent-Based Recycling Incentive Mechanism with Double Information Asymmetry
    Xu Hong1,2,Shi Guo-hong1,Gong Wen-wei1
    2012, 15 (4):  53-57. 
    Abstract ( 2196 )   Save
    A supply chain composed of a manufacturer and a recycler with double information asymmetry is discussed. In such a supply chain, the manufacturer acts as principal and the recycler as agent. In this supply chain, as an agent, the recycler makes a part of investment. The objective is to explore an effective incentive mechanism in the manufacturer's perspective. By using game theory, a new model for this problem is developed by modifying the traditional model of incentive mechanism. With this model, analysis is done. It shows that the investment made by the recycler and its recycling efforts positively correlated, or the more the recycler invests, the more recycling enthusiasm of the recycler can be incited. Also, the recycler with greater recycling capability is willing to bear more risk. Thus, in decision making, the manufacturer should take these factors into account.
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    Single Array Response Modeling Approach to Kansei Design
    He Zhen, Wu Du
    2012, 15 (4):  58-64. 
    Abstract ( 2300 )   Save
    Today, product market is characterized by individualization. However, individualization may results in significant variances in Kansei evaluation for a product. In other words, although most of the customers may be satisfied for a product in the sense of Kansei characteristics, but some of them are not. To solve this problem, in considering the heterogeneity in customer group, robust design methodology in quality engineering is introduced to Kansei product design in this paper. Kansei distance is defined to quantitatively measure the Kansei quality. Then, by treating the Kansei parameters of the product as control factors, the highly individualized characteristics among customers as noises, and the Kansei distance as response variables, a robust design model based on single array is proposed. It shows that, by this method, customer group's mental image can be satisfied and the fluctuation of Kansei reactions among different customers can be reduced as much as possible. A Kansei design case for a mobile profile is used to illustrate and validate the proposed method.
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    Research on the Customer's Common and Personal Features Based on N-Dimensional CloudModel
    Wang Hu, Li Bing
    2012, 15 (4):  65-71. 
    Abstract ( 2147 )   Save
    With the acquisition of customers service and ontological attribute data, the customer group's common features are analyzed by using multi-dimensional normal cloud model. Hence, a customer group's characteristic matrix is built. Then, by means of similarity measures based on cloud model,similarity analysis between customer groups is carried out in a qualitative way such that the customer classification can be dynamically adjusted. After determining the typical customers in each customer group, it can generate the activated intensity of individual customer's property value with respect to customer group's property value by using multi-dimensional X condition cloud generator. Then, the difference between individual customers and the typical customer in a customer group can be calculated. Numerical simulation shows that the multi-dimensional cloud model is useful for customer behavior analysis.
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    The Effect of Customer Recognition on Consumer's Flow Experience by Using S-O-R Model
    Sha Zhen-quan, Ye Zhan-hui
    2012, 15 (4):  72-77. 
    Abstract ( 2898 )   Save
    This paper analyzes the influence factors of consumer flow experience by using stores that experience the selling of brand mobile phones as case study. To make the analysis useful in theory and marketing, a stimulus-organism-response (S-O-R) model is presented to describe the flow experience with retail environment, consumer knowledge, and brand reputation being the basis of customer recognition. It shows that customer recognition can significantly affect the flow experience. Also, the three antecedent variables, namely retail environment, brand reputation, and consumer knowledge, have a significant positive impact on the customer recognition.
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    Manpower Planning for Multi-Type Staff Collaboration with Contract Period Considered
    Liang Zu-hong, Chen Qing-xin, Mao Ning
    2012, 15 (4):  78-82. 
    Abstract ( 2525 )   Save
    With contract period considered, an investigation is conducted on manpower planning for multi-type staff collaboration environment. In customized equipment making companies, there are often multiple types of staffs with different working efficiencies. This situation is even further complicated by the working groups with master-apprentice constraints. Thus, in planning the manpower for such a complicated situation, it needs to consider not only the staffs salaries and employment/unemployment costs, but also the technique inheriting and employee stability. For such a problem, a dynamic planning model which reflects staffs employing and working types is developed. With this model, it can find a satisfactory configuration of human resources. A case problem is used to show the application of the proposed method.
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    Cost Allocation Analysis in Knowledge Chain Based on Game Theory
    Yang Cui-lan
    2012, 15 (4):  83-88. 
    Abstract ( 2314 )   Save
    Cost allocation in a knowledge chain is one of the important factors that affect the stability and effectiveness of the knowledge chain. A model is presented for cost allocation for a knowledge chain with three partners by using cooperative games. With this model, analysis is carried out for both serial-parallel and parallel-serial structures. It is found that the parallel-serial structure performs better than the serial-parallel one. Hence, the cost is first allocated into three stages: supply, production, and sale, in a serial way. Then, at each stage, the cost is allocated into the partners in a parallel way by using experts' poll. An example is used to illustrate the application of the proposed method.
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    Selection and Simulation Study on Growth Way of Publishing Enterprises in China Based on CAS Theory
    Yuan Ji-dong, Wang Shu-en
    2012, 15 (4):  89-95. 
    Abstract ( 2155 )   Save
    In the view of complex adaptive system (CAS) theory, the behavioral patterns for a publishing enterprise in China to select its growth way are analyzed. It is shown that there are three growth strategies to be selected, namely, independent development-oriented, the dynamic imitation, and innovation emerging ones. Then, based on the Swarm simulation platform, a multi-agent simulation model for competitive growth strategy selection of publishing enterprises in the incomplete competition market environment is developed. This is done by agent description, behavior rule setting, market environment simulation, and genetic algorithm. With this model, by simulation, it indicates that the growth of a publishing enterprise's market undergoes three phases: normal product competition, innovation emerging competition, and dynamic imitating competition phases. Based on the results, the growth strategy selection is proposed for different phases.
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    Correlation between High-Tech Manufacturing Industries and Higher Education Scale in Guangdong Province
    Xu Xiang-dong
    2012, 15 (4):  96-101. 
    Abstract ( 2487 )   Save
    In this paper, the correlation between the scale of higher education and high-tech manufacturing industries is discussed. The scale of higher education and high-tech manufacturing industries are measured by the number of students studying in higher educational institutions and industrial added value of the high-tech manufacturing industries that are above a designated size, respectively. The study is done by using the data from Guangdong Province during the years from 2004 to 2009. Results indicate that the number of students in higher educational institutions is directly proportional to the industrial added value of high-tech manufacturing industries. A unary linear regression model can describe this relationship well. Thus, the government may increase investment to recruit more college students for some relative specialties so as to stimulate the development of high-tech manufacturing industries in Guangdong Province.
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    Evolutionary Game Analysis of Moral Hazard under Syndication in Venture Capital Institutions
    Cao Guo-hua, Zhang Dan-feng, Lin Chuan
    2012, 15 (4):  102-107. 
    Abstract ( 2880 )   Save
    Syndication is the most widely spread way of venture capital. Under syndication, often “free rider”, a phenomenon of moral hazard, occurs. By addressing this phenomenon, in order to obtain stably evolutionary strategies under different conditions, an evolutionary game model is developed for this problem. With this model, the evolutionary dynamics between two kinds of venture capital institutions is analyzed. It is found that the “free rider” behavior is caused by the ratio between the profit and cost in the current game. It also shows that management costs and the proportion of investment, the so called equity share, have significant effect on the occurrence of moral hazard. Thus, this problem can be resolved by controlling the parameters and improving the conditions. Based on the results obtained, suggestions are made for solving the problem and managing the development of syndication towards a virtuous circle.
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    Risk Transmission Analysis of Social Responsibility in Supply Chain
    Yuan Yu-hui
    2012, 15 (4):  108-113. 
    Abstract ( 2619 )   Save
    For a multilayer supply chain, a network model with multilayer topology is built in the perspective of core enterprises. Also, a conceptual model for social responsibility risk transmission is presented. Then, a mathematic model of social responsibility risk transmission in the supply chain is derived. The effectiveness of this model is verified by analysis for the dairy industry in China. Results show that, with the topological structure given in this paper and node self-adaptability, the supply chain has not only the general characteristics, such as transitivity, but also others as transformation, controllability, feedback, complexity, and nonlinearity as well. The complexity leads to the emergence of social responsibility risks.
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    practice & application
    Continuous Time Model and Solution Method for Scheduling Dyeing Vats
    Liao Jin-yuan, Wu Nai-qi
    2012, 15 (4):  114-118. 
    Abstract ( 2195 )   Save
    Dyeing is a kind of batch process and it operates in a make-to-order mode. Although an order can be made by a number of batches, in order to guarantee the quality, it requires the same production environment for these batches. Thus, in scheduling a dyeing process, one needs to determine the batches for each order and assign them to appropriate vats to satisfy the due date. In this paper, this problem is formulated as a continuous time mixed integer programming model. To efficiently solve this problem, a new method is presented to estimate the time slots. Based on the time slots obtained, the problem can be solved by using LINGO. In this way, a good solution can be found. The proposed method is computationally efficient and can be used in practice. A simple example is given to show the application of the proposed method.
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    Cycle Time Analysis for Air Plane Part Production Based on Rough Clustering
    Tu Yuan-zhi, Sun Shu-dong, Li Qing-he, Wang Meng
    2012, 15 (4):  119-124. 
    Abstract ( 2167 )   Save
    Usually, production cycle time for air plane parts has a significant fluctuation. Thus, it is omportant to accurately estimate such a cycle time. To do so, an advanced k-means clustering algorithm based on rough set theory is proposed for cycle time analysis. With the proposed algorithm, the actual samples are clustered with respect to production cycle time by using upper approximation, lower approximation, and overlapping relationship between clusters. Simulation results for practical instances indicate that the cycle time obtaied by the proposed algorithm is useful for production scheduling and capacity planning.
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    Stochastic U-Line Balancing with Operators Walking Time Considered
    Liu Kai, Su Ping, Zhao Wei
    2012, 15 (4):  124-130. 
    Abstract ( 2283 )   Save
    In a U-type production line, often the operation time is subject to random fluctuation and it takes time for an operator to go from one workstation to another. With these factors considered, the U-line balancing problem is addressed in this paper. Given cycle time and workstation completion rate, a mathematical model of minimizing the number of workstations is presented. Then, a solution method that combines genetic algorithm and simulation is proposed. Based on the layout of the line and the precedence relation of the tasks, an operator's walking route can be determined by simulation. Thus, the time taken for operator's walking is obtained, so is the time for processing a task. In this way, the balancing problem can be solved. A numerical example is given to show the effectiveness of the approach.
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    Continuous Optimization Strategy for Product Configuration Elements in Mass Customization Enterprises
    Yi Hui-yong1, Liu Wei2
    2012, 15 (4):  131-135. 
    Abstract ( 2192 )   Save
    Mass customization has become the trend for future manufacturing. By starting from the classification of product function and structure configuration elements, a product configuration element optimization model for enterprise is built. With this model, it explores different target-oriented product configuration element optimization strategies. An industrial case study is given to demonstrate the effectiveness and feasibility of the proposed method.
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    Application of Mistake-Proof System to Labor Intensive Enterprises
    Hu Jian-bing
    2012, 15 (4):  136-141. 
    Abstract ( 1979 )   Save
    Up to now, the existing research conducted on mistake-proof is for capital intensive enterprises only. However, mistake-proof is also vitally important for labor intensive enterprises. This motivates this study. With the differences between capital and labor intensive enterprises, a mistake-proof system is developed for labor intensive enterprises. The system is developed with mistake-proof design as its base, mistake-proof device as its core, and mistake-proof management and operation as complements. An application case study from a factory indicates that the system is both affordable and effective.
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