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    30 August 2018, Volume 21 Issue 4 Previous Issue    Next Issue
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    A Cascading Failure Simulation of Urban Road Network Considering Multi-Node Congestion
    LI Yanjin, LUO Xia, WANG Ying
    2018, 21 (4):  1-7.  doi: 10.3969/j.issn.1007-7375.2018.04.001
    Abstract ( 1048 )   PDF (842KB) ( 5826 )   Save
    In order to quantify cascading failure in the urban road network with multiple nodes being in sudden congestion, and to solve the chain reaction caused by the congestion at important nodes, a network cascading failure model of double-layer network assignment is constructed. By calculating the degree of road network congestion to complete cascading failure simulation in this scenario, this phenomenon is analyzed. The geometric topology of network is first completed by primitive method, and the congestion nodes are deleted from the topology in turn. Then, the traffic efficiency of road network is measured by 3 robustness evaluation indexes:connectivity, the relative size of maximal connected subgraphs and the circle rate. Based on this, the maximum node failure rate under the condition that the traffic efficiency is no less than 10% is calculated. What's more, the congestion degree of road network in multi-node failure is worked out by using the double-layer network assignment model, and finally using Transcad 4.5 and Matlab 2012a, a medium-sized road network that owning 54 codes and 92 links is derived in Chengdu calculation and simulation. The simulation results show that in the most unfavorable conditions, the network's maximum failure node ratio is 19.3%; and the cascade failure caused by 2 more nodes' concurrent congestion will have more significant effect on road network capacity than the single node failure; and that the congestion level of the whole network tends will be stable when node failure surpasses 7, and gradually reaches the limit of network's robustness. The study is aimed at providing simulation technical reference for control measures under multi-node congestion in road network.
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    Adaptive Signal Control Optimization Model in Vehicle Infrastructure Integration Environment
    YAO Zhihong, JIANG Yangsheng, WANG Yi
    2018, 21 (4):  8-14,33.  doi: 10.3969/j.issn.1007-7375.2018.04.002
    Abstract ( 982 )   PDF (909KB) ( 6247 )   Save
    Information such as position and speed of vehicles is easily obtained in vehicle infrastructure integration (VⅡ) environment. This provides a new data resource for traffic signal control systems. As the traditional signal control system is in poor robustness and cannot be adapted to the real-time variable characteristics of traffic flow, an adaptive real-time signal control optimization model in VⅡ environment is proposed. To minimize the average delay and the constraint of green time length of each phases, a genetic algorithm is used to solve the model, real-time signal timing optimization is realized at the intersection of this model. Finally, through the survey data and simulation experiment, the result shows that the proposed model performance is better than actuated control, the average delay reduced by 30%. Also, the proposed model can balance the vehicle's delay of each direction.
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    An Interval Goal Programming Approach for Multi-Period and Multi-Product Aggregate Production Planning Problem
    ZHU Bin, GUO Yue, ZHANG Fuqiang
    2018, 21 (4):  15-22.  doi: 10.3969/j.issn.1007-7375.2018.04.003
    Abstract ( 913 )   PDF (679KB) ( 6025 )   Save
    A multi-objective, multi-period and multi-product aggregate production planning (APP) problem with uncertain demand and uncertain parameters, such as operating cost, production capacity and so on, is studied. An interval goal programming model is developed through introducing interval numbers to represent uncertainties in the APP problem, in which two objectives are taken into consideration, one to minimize the total production cost and the other to maximize machine utilization rate. To solve the uncertain model, the theory of interval programming and the possibility definition based on interval ordinal relation are adopted to transform the uncertain model into its equivalent crisp one, and Lingo software is used to solve the model. The approach overcomes the deficiency of traditional uncertain optimization methods in obtaining precise probability distributions and fuzzy membership functions. In addition, the approach is able to interactively analyze impacts of different confidence levels on the objective function according to the decision maker's preference. Theoretical basis is provided for decision makers to make a rational production plan in uncertain environment. Finally, an industrial example is used to illustrate the validity and flexibility of the proposed method.
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    Bootstrap-Based Control Chart Design for Unknown Autocorrelated Processes
    LOU Lu, LI Yanting
    2018, 21 (4):  23-33.  doi: 10.3969/j.issn.1007-7375.2018.04.004
    Abstract ( 842 )   PDF (963KB) ( 5917 )   Save
    The shortcoming of applying a traditional control chart to the residuals of ARMA (auto-regressive and moving average) model estimated from process observation is analyzed, and an improved nonparametric control chart based on bootstrap resampling is presented. Average run length(ARL) considering various factors including model parameters, number of samples and distribution of residuals, are compared by Monte Carlo simulation. The results show the new control chart increases sensitivity to process shifts, and reduces false alarm rates. While bootstrap-based control chart can be built when a set of Phase-I in-control data are given and applied to raw data directly, the control effect is less affected by the number of samples, and so the proposed method is powerful yet simple to use in practice.
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    An Application Research of Modular Production in Complex System Manufacturing Process
    MI Leiyu
    2018, 21 (4):  34-42.  doi: 10.3969/j.issn.1007-7375.2018.04.005
    Abstract ( 886 )   PDF (1162KB) ( 6089 )   Save
    Based on the strong urges for improving production preparation process, shortening production cycle, enhancing production planning and control ability and promoting development level of high-end manufacturing industry, network diagrams to describe manufacturing process sequence of modules in complex system were drawn. Methods of modularity theory, manufacturing techniques, project management and optimization theory were considered. Integer programming model to determine production cycle was built. A case study was provided then. Production cycle of the entire manufacturing system and corresponding critical manufacturing path were obtained by using optimization solution software CPLEX. The solving results were used to make production preparation plan and build production plan. After adopting modular techniques, production plan and production preparation plan can go on according to the principle of maximum parallelism and production preparation can be finished before production plan begins. Production cycle is greatly shortened. The effectiveness, accuracy and superiority of the model were validated.
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    Integrated Optimization of Project Payment Scheduling Based on the Maximization of Net Present Value: A Case Study
    JIN Yan, HE Zhengwen
    2018, 21 (4):  43-50,61.  doi: 10.3969/j.issn.1007-7375.2018.04.006
    Abstract ( 652 )   PDF (936KB) ( 5712 )   Save
    Taking a real estate outside infrastructure project as background, the payment scheduling problem based on the max-npv is studied. The project is presented at first. And then the optimization model of Max-npv scheduling problem is constructed under the constraint of capital, and the satisfactory payment schedule based on the dynamic equilibrium of cash flow is obtained. Finally, the optimal solution is compared with the actual implementation of the project, the net present value of the project is improved by 17.8%, and the maximum funding gap is improved. The study provides a basis for the quantitative decision making of project payment schedule management.
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    Comprehensive Economy of Quality Evaluation Model Using Extended VIKOR Approach for Automobile Products
    ZHOU Fuli, DAI Ying, WANG Xu, ZHANG Shengnan
    2018, 21 (4):  51-61.  doi: 10.3969/j.issn.1007-7375.2018.04.007
    Abstract ( 861 )   PDF (725KB) ( 6452 )   Save
    Faced with the difficulty of automobile quality and chaotic rankings of vehicles, a comprehensive evaluation model on economy of quality of automobile using extended VIKOR is developed to assist car consumers in decision-making of purchasing. The economy of quality indexes including product quality, after-sales quality and total ownership cost are addressed. Due to multiple sources of evaluation information and uncertainty of certain indexes, the mixed types of indexes including crisp value, interval number and linguistic variables are introduced to the evaluation framework. The rough set-based attribute reduction technique is employed to delete the redundant criteria, which facilitates key indexes establishment. According to the European distance analysis for mixed indexes, the anti-entropy-based technique is used to obtain criteria weights, and the best vehicle alternative is recommended with the minimum group utility value. The case study verifies that the proposed method contributes to intelligent recommendation for vehicle consumers. A comparative analysis indicates that car users tend to select cheaper vehicles without considering operation cost. However, when taking the total ownership cost into account, they prefer to choose vehicles with top priority concerning economy of quality rather than cheap ones, which caters to practical scenarios.
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    Dynamic Adjustment of High-Speed Railway Ticket Price with Passenger Purchasing Behavior Simulation
    XU Sha, LI Yanjin, LUO Xia
    2018, 21 (4):  62-67.  doi: 10.3969/j.issn.1007-7375.2018.04.008
    Abstract ( 952 )   PDF (689KB) ( 5950 )   Save
    High-speed railway needs a ticket price adjustment strategy based on market competition environment. Considering probability of passenger purchasing ticket, railway seats inventory and dynamic price in time domain, giving expression formula of passenger purchasing benefit, using dynamic programming method to deduce recursive formula between seats inventory and dynamic ticket price, a dynamic adjustment model of railway ticket price under market competition environment is eventually built. Through simulation data from Beijing-Guangzhou High-speed Railway and the air transport with same direct OD in a 60-day pre-sale period, a conclusion is reached that arriving probability of passenger purchasing ticket submits to non-homogeneous poisson distribution, finishing 4 dynamic adjustments on seats inventory:500, 375, 270, 207, and relevantly the railway ticket price is dynamically adjusted:900yuan, 950 yuan, 1 000 yuan, 920 yuan. The research results can provide simulation method for high-speed railway ticket price system under comprehensive transportation environment.
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    Defaulting Problem of Contract-Farming Supply Chain with Dual Channel
    FENG Chun, CHEN Yanna
    2018, 21 (4):  68-74.  doi: 10.3969/j.issn.1007-7375.2018.04.009
    Abstract ( 834 )   PDF (695KB) ( 5954 )   Save
    To solve the defaulting problem in contract-farming supply chain and reduce the default rate of agricultural contract, game theory is used to model the trading process and default mechanism. Taking backward induction, the optimal purchase price and quantity are obtained. The profit distribution and behavior selectionunder different models also are discussed. It is found that the contract design in the decentralized decision-making model is beneficial to the farmers, and the company is not favored and has the risk of default. The contract design under the Nash negotiation model is beneficial to both sides, and neither of them breaches the contract. The supply chain can reach a steady state. The overall profit of the supply chain under the Nash negotiation model is greater than the overall profit of the supply chain under the decentralized decision-making model, and is equal to the supply chain profit under centralized decision-making model. The model can achieve the perfect coordination of the supply chain.
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    A Shapley Value Revenue Distribution Model Considering Risk Factors of Aviation Strategic Alliance
    CONG Xiaoni, XIAO Yao, LI Shiping
    2018, 21 (4):  75-84.  doi: 10.3969/j.issn.1007-7375.2018.04.010
    Abstract ( 807 )   PDF (452KB) ( 5876 )   Save
    Airline strategic alliance has become an important way of cooperation between international airlines, and has a positive impact on airline cost reduction, revenue increase and market expansion. When airlines join the alliance, how to allocate profits reasonably after cooperation will have an important impact on airline performance and the stability of airline alliances. For this purpose, a decision-making model is built aiming at maximizing the revenue. The optimal pricing and flight frequency of two models under centralized decision and decentralized decision are respectively discussed with the revenue of airline and airline alliance under optimal decision. On this basis, through fuzzy comprehensive evaluation, the risk of airline alliance is considered, combined with the Shapley value method of risk, the fair and reasonable distribution of the maximum profit of the alliance is allocated, and a revenue allocation solution is provided to the airline company. Finally, combined with the actual situation of China Southern Airlines, the revenue allocation model is used to formulate the revenue allocation plan for the strategic alliance of South China Airlines.
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    The Effect of Supplier's Vertical Shareholding on Competitive Manufacturer's Pricing Strategy
    GUO Qiang, ZHANG Ting, WANG Wenyi
    2018, 21 (4):  85-93.  doi: 10.3969/j.issn.1007-7375.2018.04.011
    Abstract ( 1127 )   PDF (828KB) ( 5880 )   Save
    The equity strategic alliance is a partnership formed between companies to achieve common goals. This is a very common phenomenon in supply chain management. In this context, a study is conducted on the influence of different market structures and shareholding ratios on competitive manufacturers' pricing strategies when supplier holds equity in the manufacturer. According to the difference in the market position of manufacturers, three stockholding models were constructed:duopoly leader, held-owner manufacturer as leader and un-held manufacturer as leader, using the backward induction of game theory to solve the equilibrium yield, retail price and optimal profit. The results show, 1)that the optimal retail price of manufacturer held by supplier is the highest when it is leader, and second when the competitor is leader. The optimal price of manufacturer not held by supplier is affected by both the shareholding ratio and the market structure; 2) that when the proportion of shareholding is large, the manufacturer held by supplier has the "first mover advantage" and the "backward advantage" when the proportion of shareholding is small, and the "backward advantage" of the manufacturer not held by supplier is irrelevant to the shareholding ratio; and 3) that the supply chain profit increases first and then decreases with the shareholding ratio, with social welfare positively correlated with the ratio.
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    The Impact of Risk Aversion on Manufacturer's Launching Direct Channel
    CHEN Yinping
    2018, 21 (4):  94-103.  doi: 10.3969/j.issn.1007-7375.2018.04.012
    Abstract ( 1101 )   PDF (685KB) ( 5566 )   Save
    The risk preference of decision makers can influence the decision-making process of the supply chain. Thus the impact of risk aversion on manufacturer's launching direct channel is studied. Based on game theory's IR and IC under two cases which are single and dual supply chains, the optimal decision-making and social welfare of all members were analyzed. The results show that only when the risk aversion of decision makers and sales costs of direct channel meet certain conditions, the manufacturer launch direct channel. The utility of retailer is not always eroded by direct channel. When the risk aversion of decision makers is high and the direct channel cost is moderate, the supply chain value is reduced. Social welfare always tends to decrease and then increase with the increase of risk aversion of manufacturers.
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    A Research on Multi-Project Human Resource Scheduling in R & D Enterprises——A Hyper-Heuristic Algorithm Based on Ant Colony Optimization
    YI Yali
    2018, 21 (4):  104-109.  doi: 10.3969/j.issn.1007-7375.2018.04.013
    Abstract ( 1034 )   PDF (512KB) ( 5654 )   Save
    At present, the project of R & D enterprises is in multi-project environment. In order to solve the human resource contention in multi-project management, this kind of enterprise is studied for optimizing the human resource scheduling in the multi-project management. The minimum total cost is taken as the objective function by taking the delay penalty cost into consideration, and the real problem is modelled. An algorithm which is "hyper-heuristic" based on ant colony optimization is used to solve the problem. The algorithm divides the problem into two parts, project activity allocation and selection, and it uses ant colony optimization as high-level heuristic strategy to search low level heuristic rules, then generates feasible solutions according to the rules. Multiple sets of simulation experiments are designed to compare this algorithm with the combination of heuristic rules. the experimental results show that the algorithm performs a better search performance overall, and it provides a new solution to the scheduling problem for human resources.
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About Journal
主管单位:广东省教育厅
主办单位:广东工业大学
主  编:唐立新
编辑部主任:傅惠
编辑出版:广东工业大学期刊中心
     《工业工程》编辑部
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邮  编:510090
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标准刊号:ISSN 1007-7375
     CN 44-1429/TH