Table of Content

25 February 2014, Volume 23 Issue 2

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Theory Analysis and Methodology Study

China's Regional Disparity of 3E Total Factor Productivity in a Dynamic View

LEI Ming, YU Xiao-wen, ZHAO Xin-na, DENG Hong-hui

2014, 23(2):  1-14. 

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This paper applies global Malmquist-Luenberger Index and SBM directional function with dynamic factor to measure Energy-Economy-Environment(3E)total factor productivity and its components in China's 30 provincial regions over the period 1998 to 2011. Bootstrap methodology is introduced to estimate confidence intervals for technical efficiency, which provides a correction for the inherent bias in Malmquist-Luenberger DEA estimation. The major conclusions are as follows: 3E total factor productivity increases with a low rate which dues to the complementary state of 3E frontier catch-up and shift effects; the traditional technique progress lags dynamic effect of capital.

Quality Control Mechanism in Supply Chain Based on Contract and Relationship Governance

SHI Dan, LI Yong-jian

2014, 23(2):  15-23. 

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In this paper, quality control mechanism is studied in a supply chain that consists of one supplier and one manufacturer. We discuss the choice of governance mechanism to improve product quality and coordinate the supply chain, when the manufacturer and supplier make concerted efforts to improve the quality. Quality control decision is analyzed in three different scenarios which include cooperation, formal contract governance and relationship contract governance. Considering the scenario of cooperation as a benchmark, we compare the effect of two governance mechanisms on supply chain performance. It shows that the combining governance mechanism of relationship and contract governance can get better effect of coordination due to higher effort of quality control.

Compensation Strategies and Risk in SLA under Cloud Computing Mode

YAN Jian-yuan, LU Xin-man, ZHEN Jie

2014, 23(2):  24-32. 

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In this paper, we first propose three compensation strategies (linked respectively to the number of outages, the number of failures lasting more than prescribed thresholds, and the cumulative downtime)in Service Level Agreement(SLA)according to characteristics of cloud computing. By setting tolerance threshold in SLA, we provide grading compensation to customers based on the level of service failures. In order to provide a measure of risk, we compute the Value-at-Risk(VaR)for three strategies and obtain the characteristics and variation of VaR. Under the equal average losses, we can see that the compensation strategy based on the cumulative duration demonstrates a larger VaR compared with the one based on the number of failures. Hence, the former is risker. The illustrative example indicates that our proposed compensation strategy is reasonable and feasible. The results provide constructive guide for cloud service providers to make compensation strategies.

Retailer's Optimal Deposit Replenishment Strategy Under Revenue-sharing Contract

WU Xiao-li, WAN Chang-hai, ZHOU Yong-wu

2014, 23(2):  33-40. 

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Deposit replenishment strategy means that the retailer pays some deposit to suppliers in the first period, and the supplier automatically replenishes to the retailer according to the retailer's deposit amount in the first period. For the small or medium sized retailers, their replenishment strategies are often restricted by their own funds, where their own funds are usually not sufficient to meet the optimal newsboy model. We find that the retailer's optimal replenishment quantity affects not only his own revenue, but also the profit of the whole supply chain. We study the problem that the retailer faces the stochastic market demand under revenue-sharing contract. We suppose that the retailer can always ask for the bank loans when needed. This article studies the two-period problem and shows that the retailer's optimal replenishment strategy is influenced by both his initial capital and the revenue sharing coefficient. Finally, we extend the two-period problem to multiple period problems and discuss the optimal decision accordingly.

The Model and Approach of Emergency Decision-making Based on Fuzzy Rough Set over Two Universes

SUN Bing-zhen, MA Wei-min, ZHAO Hai-yan

2014, 23(2):  41-48. 

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In this paper, we discuss the theory of fuzzy rough set over two universes with the background of emergency decision-making. Then we define a fuzzy rough set model based on fuzzy compatible relation over two universes. By the theory of fuzzy rough set over two universes, the emergency decision-making changes into a rough approximation of a fuzzy decision object on the decision approximation space over two universes. So, we construct the model of emergency decision making based on fuzzy rough set over two universes. We first compute the lower(upper)approximation of the fuzzy decision object with respect to the approximation space over two universes, and then present the decision rules by combing the idea of uncertainty decision-making. Moreover, the algorithm of the model is given. This model gives a kind of decision approach to emergency decision-making under the condition of incomplete information. Furthermore, it also gives the optimal decision rules with the confidence coefficient by considering the preference of the decision-makers. The proposed method could give a properly descriptive of the characters for the emergency decision making with incomplete information, limited recourses of humans and materials and urgently time. Therefore, it can provide a basic theory and a decision approach in practice for emergency decision-making. Finally, the validity of the approach and the applied process is tested by a numerical example.

Optimal Multi-period Production Policy with Uncertain Demand and Work-in-process Inventory

WU Peng, LV You-chang

2014, 23(2):  49-54. 

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In order to cope with demand uncertainty, firms can produce both finished products and work-in-process products before the demand is realized, and quickly finish the rest production process for the work-in-process products if necessary after the uncertain demand is known. The unsold inventory can be used to satisfy future demand. As a means to increase production flexibility, handling work-in-process products may increase the production cost. When optimizing the production decision, firms need to make a tradeoff between cost and flexibility. Our model studies the optimal multi-period production policy with uncertain demand and work-in-process inventory under the framework of dynamic programming. By analyzing the structural property of the objective functions and value functions, we find the optimal production policy is a modified base-stock policy. We also analyze the impact of different parameters on the optimal policy.

Competitive Strategy for the Manufacturer and Remanufacturer Under Patent Licensing

SHEN Cheng-ran, LIU Ming-wu, XIONG Zhong-kai

2014, 23(2):  55-63. 

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In the patent perfect market, the original manufacturer by the patent protection can adopt two strategies: no license remanufacturing and license remanufacturing. Based on the remanufacturing cost difference and consumer heterogeneous, this paper establishes the single period model without recovery number limit and two period model with recovery number limit respectively. The optimal decision and equilibrium profit are given by using game theory. Through the comparative analysis and numerical simulation, the paper discusses the effect of different parameters on pricing strategy and the profit. The results show that the original manufacturer can share remanufacturing benefit through patent licensing fee in the case of license remanufacturing, so the original manufacturer is willing to adopt the strategy of manufacturer license; only when the cost savings is high enough in license remanufacturing, the remanufacturer will receive the patent licensing of the original manufacturer.

Stochastic Comparison of Phase-type Distributions

YU Hai-bo

2014, 23(2):  64-72. 

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In this paper, we analyze stochastic comparison of phase-type(PH)distributions by using stochastic dominance in applied probability, sufficient conditions and necessary and sufficient conditions for comparing two phase-type distributions under first and second degree stochastic dominance are provided. We prove that conditions to compare variabilities of two discrete phase-type distributions are different from those comparing variabilities of two continuous phase-type distributions. Conditions comparing two continuous phase-type distributions under second degree stochastic dominance are independent of their means, but conditions comparing two discrete phase-type distributions depend on their means. The results in this article can be applied to the problem for the minimization coefficient of variation and variabilities of phase-type distributions, and they can also be used to analyze the effect of variability of arrival process or service time on queue length or waiting time in queueing systems.

Supply Chain Coordination and Optimization with Risk-averse Retailer and Sales Effort Dependent Demand

XU Min-li, WANG Qiao, OU Yang Lin-han

2014, 23(2):  73-81. 

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This paper introduces the retailer's risk aversion in a two stage supply chain. Under both the additive and multiplicative sales effort dependent demands, the issue of supply chain coordination and optimization with risk-averse retailer and sales effort sensitive demand under a single sales rebate and penalty contract is explored. Besides, the optimal conditions that the contract parameters must satisfy in order to achieve supply chain coordination are determined. Numerical analysis is presented to further illustrate the role of sales rebate and penalty contract.

Supply Chain Effects of Retailer's Innovation Investment for Mixed Channels Under Information Asymmetry

TIAN Wei, JIANG Kan, WANG Dong-hong

2014, 23(2):  82-88. 

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In this paper, using a Stackelberg game model, we study supply chain effects of retailer's innovation investment for mixed channels. We obtain the partners' closed form solutions of decisive variables and profits under both complete and incomplete information about the retailer's cost parameter of innovation investment, and analyze how this cost parameter, uncertainty degree of the manufacturer about the retailer's cost structure, customers migration rate, base demand of market, innovation potential influence them. We find that the manufacturer would always benefit by obtaining more cost information, and the conditions under which the retailer would be willing to share information with the manufacturer and whole supply chain would improve. All these would help the manufacturer to decide about an information sharing contract with the retailer. Finally, the numerical examples are provided to verify the conclusions.

Equilibrium Analysis of Closed-loop Supply Chain Based on the Stochastic Demand and Risk Decision-making

CAO Xiao-gang, ZHENG Ben-rong, WU Jin-feng, LI Ji-zi, WEN Hui

2014, 23(2):  89-98. 

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Based on equilibrium theory and variational inequality, a multi-tiers competitive closed-loop supply chain with stochastic demand and remanufacturing rate in uncertainty is proposed, and the behavior and equilibrium conditions of suppliers, manufacturers, retailers, demand markets and the closed-loop supply chain are analyzed. For the model, the equilibrium results are obtained through Qusi-Newton algorithm and simulation analysis are made of how remanufacturing rate, return rate and risk behavior of the manufacturers influence the network equilibrium. The conclusion indicates that an increase in remanufacturing rate may lead to the overall profits of the supply chain and recycle volume increase simultaneously. What's more, manufacturers make decisions based on risk minimization and profit maximization principal of combination can increase trading volume and corporate profits.

Supply Chain Coordination Model with Trade Credit and Buyback Contracts

GUO Jin-sen, ZHOU Yong-wu, ZHONG Yuan-guang, LI Chang-wen

2014, 23(2):  99-106. 

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The paper considers a supply chain that consists of a supplier and a retailer, who sells a single product to the customers over a short selling season. In this paper, we mainly research how the retailer uses the trade credit to entice customers to increase their ordering quantity and how the supplier designs the buyback contract so as to maximize his/her own expected profit with different perspective. Solving the models, we have got the optimal solutions that can make the total profit reach the maximum and obtain some effective theorems. Finally, we provide a detailed numerical example to illustrate the model and some meaningful management implications.

Research on Coordination Mechanism of Two-Echelon Logistics Service Supply Chain

MENG Li-jun, HUANG Zu-qing, GUO Xiao-chai

2014, 23(2):  107-115. 

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The coordination problem of a two-echelon logistics service supply chain with one logistics service integrator and one functional logistics service providers is analyzed. The mathematical models of centralized coordination. Stackelberg game coordination with wholesale mechanism, and coordination with revenue sharing mechanism are developed, and then the realization conditions for optimal solution under different coordination strategies are presented. By the comparison between the different models, the results show that the logistics service supply chain with revenue sharing mechanism can be coordinated because it achieves the same performance as in the centralized situation, and both parties can earn more than that from wholesale mechanism. Finally, a numerical example is presented to illustrate the efficiency of the revenue sharing mechanism.

Collaboratively Scheduling Method of SAR Resources for Drifting Objective in Distress at Sea Based on Greedy Algorithm

WANG Jun, WANG Mei-rong, WANG Yi-yang, SONG Xiao-liang

2014, 23(2):  116-123. 

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Influenced by meteorological and hydrographical factors at sea,the objective in distress may drift apart from the initial spot. Therefore, the scheduling scheme for rescue resources has to be organized accordingly. Because of the particularity of maritime peril and rescue at sea, based on the forecast for the drifting route of the objective in distress, this paper aims to present a two-phase collaborative scheduling model for rescue resources around the objective in distress from sea and inland respectively, which includes the navigating ships nearby, coastal rescue bases and inland depots of contingent commodities, under the restrains of requirements of demand and time limit. Finally, the greedy algorithm is designed to solve the model and its validity is examined by a numerical example.

Evolution Model of Low Carbon Supply Chain Collaborative Operation

WU Yi-sheng

2014, 23(2):  124-132. 

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With regard to the system evolution issue of the low carbon supply chain's collaborative operation, the order parameters and operation processe of low carbon supply chain's collaborative operation system is put forward based on servo principle of the collaboration theory in this paper. Firstly, the logic plus and logic multiplication principle of boolean algebra theory are used to analyze the relationship between the order parameters and operation process. Then, the rate principle of system dynamics theory is used to construct an evolution model of low carbon supply chain's collaborative operation. Further more, self-organizing principle of collaboration theory is used to analyze how the order parameters influence the low-carbon supply chain collaborative operation's evolution process. Moreover, the rule of the low-carbon supply chain collaborative operation is analyzed by using synergies principle, and the model is analyzed by application simulation. Finally, this paper concludes the mechanism of low carbon supply chain's collaborative operation.

Research on Emotional Decision Model of Multi-Agent Negotiation

DONG Xue-jie, JIANG Guo-rui, HUANG Ti-yun

2014, 23(2):  133-138. 

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During the negotiation process of automated negotiation based on intelligent agent, the anegotiation agent usully adopts a fixed negotiation strategy, which limited its adaptability in the complex negotiation environment. Based on achievement of emotion theory research, we point out an emotional decision model to improve the degree of intelligence and adaptability of the agent. First, we analyse the emotional decision process of the agent in an automated negotiation, then propose an emotional generation model and emotional decision model in general. Taking single attribute negotiation as an example, we establish a concrete emotional decision model of the negotiation agent. In comparison with non-emotional model, it shows that our emotional decision model can get better result. The results of this research can be applied to various forms of automatic negotiation based on multi-agent.

Multi-objective Two-person Zero-sum Matrix Game Based on Intuitionistic Set

ZHOU Xiao-guang, GAO Xue-dong, ZHANG Xiao-dong

2014, 23(2):  139-144. 

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The research of matrix game is a basic approach and important means for the research of game theory. The multi-objective two-person zero-sum matrix game, whose payoff values are intuitionistic fuzzy numbers, is proposed based on the theories of intuitionistic fuzzy multi-objective decision making and fuzzy game. The model of multi-objective two-person zero-sum matrix game based on intuitionistic set is introduced at first. Then the linear program method of intuitionistic multi-objective two-person zero-sum matrix game is presented. Finally, an example is given to illustrate the proposed method. The results show that the equilibrium strategy and equilibrium solution of the game can be easily acquired by the proposed method.

Topic Preference Based Method for Collaborative Filtering Algorithm in Sparse Datasets

ZHANG Yao, FENG Yu-qiang

2014, 23(2):  145-152. 

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User-based collaborative filtering algorithm is an important method for B2C electronic commerce to recommend commodity, but it has been limited to some extent because of the sparsity of common rations between users. In order to resolve these problems,the paper first adopts association rule mining to formalize similarity among competitive goods based on considering consumption level, and then constructs time-based Bayesian goods relation network, based on the network the paper takes advantage of components analysis of whole network to find complementary similarity of the goods and the topic preference of consumer for expanding common rating sets. At last, through comparative experiments based on F₁ method and diversity method, the result shows that the accuracy and diversity have been improved significantly in sparsity environment. The data are collected from the site of JingDong Mall. In conclusion, the model provides a new way of dealing with sparsity problem, enriches examples using whole network approach in goods relationship analysis, and has the significance in theory and practice.

Risk Management Based on Fuzzy Measure and Integral: An Application to Air Traffic Control Management

LI Tong, CAO Hai-feng, SUN Hong-xia, BAI Fu-li

2014, 23(2):  153-157. 

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Air traffic safety management has focused on the risk of single type of threat and error, ignoring the interaction of threats and errors. It's difficult to embody the correlation of different types of risk. Based on fuzzy measure, air traffic risk decision making model is proposed, where Choquet integral serves as the risk function on the coalitions formed by different types of threats and errors. On the basis of risk function, Shapley value distributes the risk value to each type of threat and error. Through applying this risk decision model, we have an example to illustrate how interaction index modifies the risk value, which is more practical for air traffic operation.

Time-dependent Single Vehicle Routing Problem and Dynamic Programming Algorithm with Greed Dispatching Restriction

PENG Yong, YIN Shu-cai

2014, 23(2):  158-162. 

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Vehicle routing problems have been extensively studied due to its extensive application and great value on economy. However, two constraints receive less attention, i.e., vehicle speed will be changed with time, and vehicle can service more than one trip. This paper discusses single vehicle routing problem with these two constraints. A mathematic model the optimal object of which is to find the route schedule which has the earliest task completion time is established. It's hard to achieve exact solutions of the problem. So the paper proposes a greed dispatching strategy for the model to compress solution space, and provides a dynamic programming algorithm with FIFO rule. The numerical examples demonstrate that for our model, the solution provided by dynamic programming algorithm is only a satisfactory solution. The numerical examples also indicate the optimal dispatching time decreases while the vehicle load capacity increases, and it gets the minimum when the vehicle load capacity is larger than customers total demand. That is, using larger capacity vehicle will save more dispatching time than using smaller capacity vehicle.

One Leader-Multi-Followers Oligopolistic Competition Model on the Condition Inverse Demand Function is Set-Value

WANG Neng-fa, YANG Zhe

2014, 23(2):  163-166. 

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In the reality, the demand function may not be a single value, but set-value. One leader-multi-followers oligarchic competition model is studied. The set-value inverse demand function is analyzed, and the property of following oligarchs reaction function is given. Furthermoure, the existence of Stackelberg-Cournot Nash equilibrium(SCN)is proved.

Multiple Attribute Large-scaled Group Decision Making Methods Based on New Intuitionistic Fuzzy Similarity Degree

LI Peng, ZHU Jian-jun

2014, 23(2):  167-174. 

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In this paper, the large-scale multiple attribute group decision making(MAGDM)method with intuitionistic fuzzy information is studied. First, a new formula to derive the intuitionistic fuzzy similarity degree between two intuitionistic fuzzy sets is proposed. And a clustering method is developed based on the new formula. The decision makers can be clustered into different classes by the above method and the core decision makers can be found in the different classes. Then a method is designed to determine the weights of the core decision makers. Finally, an example shows the feasibility and validity of this method.

Application Research

Mixed Set Programming for Crew Pairing

LAN Bo-xiong, ZHANG Mi

2014, 23(2):  175-182. 

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Crew costs are the second largest direct operating costs in an airline's expenses, only next to fuel costs. However, crew pairing is a highly constrained and complex problem, which makes it extremely difficult to find optimal solutions. In this paper, mixed set programming(MSP)is proposed for the first time to build the model. Quite different from mathematical programming, MSP supports global reasoning over a mixed domain of real numbers, integers, booleans, and sets. Set partitioning model and routing model are the core parts of our model. Computational test shows that problems of real-world size can be solved efficiently within reasonable time.

A Method for Identifying Individual Advantage Characteristics Based on 2-tuples Linguistic Evaluation Information

ZHAO Xi-nan, OU Xin-yu, XI Jin-yan

2014, 23(2):  183-190. 

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A method for Identifying Individual Advantage Characteristics(IIAC)based on 2-tuples Linguistic Evaluation Information is proposed, which is applicable to the hierarchical structure index system. In this paper, we incorporate linguistic assessment information characteristics, 2-tuples linguistic information processing, the ideal point model, and clustering analysis with our method(IIAC). And we demonstrate how to use our method by an example, the identification of the culture advantage characteristics of one enterprise, which illustrates the feasibility and effectiveness of our method. For a measured behavioral subject, our method can fully mine and reflect its Individual Advantage Characteristics which will provide multiple dimension decision information for decision maker.

Airport Alliance Decision Making Based on Entropy Topsis and Game Dynamics

CUI Qiang, WU Chun-you, KUANG Hai-bo

2014, 23(2):  191-197. 

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Airport alliance is an important way for airports to reform the resource, but airport' positivity is different due to its own ability, so it is a common concern that how an airport will decide when facing alliance problem. The goal of this paper is to offer alliance decision-making suggestions for airports under the precondition that the alliance game benefits of airports are not same, and the game benefit evaluation index system is built from the aspects of regional development, production factors, demand conditions, support industry and environmental effect. Then the airport network is abstracted as a small-world network and the airport alliance decision-making problem is studied using game dynamics on small-world Network combining with entropy topsis model, then the main factors influencing airport alliance are summarized based on the empirical study of the 25 big airports in 2010. The results show that airport alliance is not a long-term policy for airports and the key point for development is enhancing own strength, which has a practical value.

Coordination Mechanism of Quality Behavior in Two-echelon Pork Supply Chain Based on Differential Game

XIA Zhao-min, SUN Shi-min

2014, 23(2):  198-205. 

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Coordination mechanism of quality behaviors in two-echelon pork supply chain composed of a slaughtering and processing company and a supermarket is researched by means of differential game. The slaughtering and processing company's and supermarket's optimal quality behavioral decisions in the Nash non-cooperative game, Stackelberg leader-follower game, and coordinated cooperative game are investigated respectively. And then the feedback equilibrium outcomes in the four game structure are comparatively analyzed. The results show that, the slaughtering and processing company's and supermarket's quality behaviors, the pork supply chain's profit in the coordinated game are superior to those in the non-cooperative game. And the value range of distribution coefficient of pork supply chain's profit is proposed to achieve Pareto optimality of individual profits of slaughtering and processing company and supermarket, and thus coordination of quality behaviors.

Deposit Insurance Pricing Method Considering Bankruptcy Externalities

LV Xiao-ning, QIN Xue-zhi

2014, 23(2):  206-212. 

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It is generally considered that the overall costs of bank failures are higher than those in other industries. This is due to the existence of negative externalities of bank failures, which may lead to additional loss of the default banks' assets. This paper establishes a pricing model of deposit insurance with consideration of bankruptcy externalities. It is taken into account that each default bank's bankruptcy cost involves not only its assets loss caused by liquidation but also the externalities that may increase other banks' bankruptcy cost. Expected loss pricing method is used to calculate the net premium of deposit insurance while the additional premium is determined utilizing Shapley value. The total premium accordingly reflects each bank's marginal contribution to the total bankruptcy cost of the whole banking system. Three scenarios are constructed to test the model. The results show that it is negatively correlated between the premium and the banking system's acquisition ability of the bankruptcy assets, and this correlation becomes more significant when the economic situation deteriorates. Meanwhile, the number of insured banks in the banking system impacts the premium negatively.

The Mystery of Correlation Structure Between Shanghai and Shenzhen Stock Market Based on Bayesian Copula Research

WANG Lu, HUANG Deng-shi

2014, 23(2):  213-219. 

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There are different opinions about the correlation structure between shanghai and shenzhen stock market based on copula. After the fact that the goodness of copula fit test is affected by parameter estimation, the Bayesian copula selection is introduced, which can separate parameter estimation from the goodness of fit test.Then, the empirical results by the Bayesian copula selection show that the correlation structure between shanghai and shenzhen stock market is time-varying, which causes the difference of the results.

Bayesian Unit Root Test on Quantile Autoregressive Process Based on MCMC Algorithms

ZENG Hui-fang, XIONG Pei-yin, XIANG Guo-cheng

2014, 23(2):  220-225. 

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Classical tests for unit roots have been criticized for their unusual asymptotic theory leading to disconnected confidence intervals and their lack of power in small samples. We develop a simple and efficient MCMC algorithm for fitting the dynamic quantile regression model based on a location-scale mixture representation of the asymmetric Laplace distribution. Moreover, we exploit the maximum posterior interval for different prior distribution. The simulation result shows that Bayesian quantile regression method is a complete and robust method to test non-stationary for time series. An empirical application of the method modeling the China CPI index dynamic illustrates that there exists stock on upper tail of the distribution but not lower tail.

Management Science

The Research on the Labor Staffing and Scheduling Model of Multilevel, Multiskill for Data Process Outsourcing Company

TAN Zheng, WU Feng, WANG Qing-qing

2014, 23(2):  226-236. 

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Service outsourcing is one of the important approaches to adjust industrial structure in China. Data process, one of the basic business in service outsourcing, relies too much on the human resource. The company should arrange the staff efficiently to process and deliver orders in time. In consideration of the whole production process and the kinds of the staff skill, a twostep multi-level multiskill labor staffing and scheduling model is built. A practical example is solved by the proposed model. The result indicates the availability of the model, which can improve the vendors'capability in China and the significance of promoting development of the service outsourcing industry.

Classification of Hard-to-Recover Reserves Based on FCM and Combination weighting approach

YANG Juan, GONG Cheng-zhu, ZHU Ke-jun

2014, 23(2):  237-243. 

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Currently, the classification criterion of reserves are determined by the scope of the values of criteria such as geological attributes, reservoir phydical parameters and etc., which require all attribute values of one block should be just right in the existing range of criteria, otherwise it would be difficult to divide the hard-to-recover reserves into different categories. To solve this problem, this paper combines with Fuzzy c-Means clustering algorithm(FCM)and combination weighting approach to classify hard-to-recover reserves. First, FCM is used to automatically search for the optimal category number of reserves based on effect indexes. Then, a combination weighting model is established based on the minimal error-sum of deviation of subjective weights and deviation of objective weights, which is used to compute the weights of attributes and the values of effect indexes. Finally, the categories that blocks belonge to is judged according to the result of FCM. To verify the validity of model, this paper applies it to the classification problem of hard-to-recover reserves from an oil field in the 10th Oil Production Plant of PetroChina Daqing Oilfield LLC, which would conduct the rolling development of hard-to-recover reserves.

Single Machine Total Weighted Tardiness Scheduling with Unconnected Precedence Graph and Loop Constraints

XUAN Hua, LIU Jing, LI Bing

2014, 23(2):  244-249. 

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In order to satisfy the demands for job processing order and arrival time in practical production environment, this paper studies a single machine total weighted tardiness scheduling problem with some novel features. These features are that each job has a release date and the precedence graph formed by job precedence relations is unconnected and consists of undirected loop. A mathematical programming model is then formulated. Further, Lagrangian relaxation combined with hybrid backward and forward dynamic programming is proposed to solve this problem as an extension of Tang and Xuan et al. In this algorithm, hybrid backward and forward dynamic programming is designed to deal with the case that a job may have multiple predecessors or successors. A subgradient algorithm is then used to update Lagrangian multipliers and a heuristic algorithm is presented to construct a feasible schedule based on the solutions of the Lagrangian relaxation problem. Experimental results show that this algorithm can obtain satisfactory solutions within a shorter computation time and it can provide an idea to solve more complicated scheduling problems.

Capacity Allocation Policy of Outpatient Appointment Considering Cancellation of Appointment

CAO Ping-ping, TANG Jia-fu

2014, 23(2):  250-257. 

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In the practical outpatient appointment problems, scheduled patients may cancel their appointments before receiving services, which has a negative effect on clinic revenue. It's a significant problem to explore how to design a reasonable and effective capacity allocation policy considering the cancellation of appointment. In this paper, the capacity allocation problem of outpatient appointment which includes appointments in advance and in same-day is considered. Considering the situation that patients who make appointments in advance may cancel their appointments, an optimal capacity allocation policy is presented to determine the capacity allocation between patients who make appointments in advance and in same-day. For maximizing the expected revenue of clinic, the Markov process model considering cancellation of appointment is firstly constructed, and the relevant property is given. Furthermore, based on the model characteristic, the existence of the optimal number of patients who make appointments in advance is proved for any appointment period, and the optimal capacity allocation policy and algorithm of solving the policy are given. Finally, a numerical test is given to illustrate the practicality and effectiveness of the proposed capacity allocation policy.

Exploring the Matching Between Leadership Styles and Organizational Situations: Based on the Model of Fuzzy Expert System

DING Dong-hong, HUANG Sheng-lan, CHEN Zhi, SONG Yi, HUANG Xiu-li

2014, 23(2):  258-264. 

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By constructing the model of fuzzy expert system, this paper explores the optimal matching between six leadership styles(spiritual type, coaching type, relational type, democratic type, forerunning type and commanding type)and four organizational situation elements(organizational culture, subordinates' maturity, leader-subordinate relationship and the uncertainty of the environment). Moreover, applying the model to analyze a private company of apparel external trade, we find that spiritual leadership would be in favour of the development of the company when the value of environmental uncertainty is larger and the values of organizational culture, subordinates' maturity and leader-subordinate relation are smaller. The conclusion demonstrates the descriptive power of the model, remedies the shortcoming of traditional qualitative studies, and will provide some suggestions for leaders who need to transform a fixed leadership style according to specific situations.