Table of Content

25 February 2020, Volume 29 Issue 2

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Theory Analysis and Methodology Study

Study on the Storage Allocation Problem Under Cargo to Person Picking Mode

LI Zhen-ping , FAN Xin-ran, WU Ling-yun

2020, 29(2):  1-11.  DOI: 10.12005/orms.2020.0028

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The storage allocation problem under cargo to person picking mode is studied. An integer nonlinear programming model is established to minimize the total time of moving shelves in the process of orders picking, the problem is proved to be NP-hard, and then two different approaches are designed to solve the model. In the greedy approach, the items are first clustered based on the relationship of orders and items, and then a greedy algorithm is applied on the clustering results.In another approach, the partheno evolution genetic algorithm is designed to solve the model directly. By adopting 0-1 matrix encoding rule, multipoint gene inversion operator,single point gene mutation operator and elitism scheme, with reasonable selection of parameters, the approximate optimal solution of the problem can be quickly found. Simulation is done on several simulation examples and a real case.The running time and effect of the greedy algorithm and the genetic algorithm are compared and analyzed. The results show that for small scale problems, both algorithms can get the global optimal solution with high probability in a relatively short time, and for the medium scale real case, the storage allocation schemes obtained by both algorithms are better than the enterprise's current storage allocation scheme. The storage allocation scheme obtained by genetic algorithm is better than that of the greedy algorithm in terms of the number of shelf movements and the total moving time. The genetic algorithm designed in this paper can be used as the core algorithm of intelligent warehouse management information system.

Studyon Routing Problemfor New Energy Mobile Charging Vehicles

CHEN Ping, DONGWen-zhe, YU Xin-yao

2020, 29(2):  12-18.  DOI: 10.12005/orms.2020.0029

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Against the background of green city, the number of electricvehicles has increased sharply. However, the charging infrastructure is notsufficient, and thus mobile charging industryappears.However, these companies are not profitableas expected. The main problem they are facing is the conflict between high operating cost and low profits. Optimizing the decision making of mobile charging vehicle routing becomes a critical issue. This study focuses on mobile charging vehicle routing problem, which aims to maximize the total profit under the constraints of soft time windows, battery capacity and endurance mileage. We formulate this problem. In addition, to solve this problem, a max-min ant colony algorithm is presented. Computational results demonstrate the effectiveness and efficiency of the model and algorithm. This paper also provides some managerial insights for mobile charging companies operation.

Economic-statistical Design of EWMA Control Chart Based on APL

WANG Hai-yu, QIAO Bai-hao, QU Bo-yang

2020, 29(2):  19-27.  DOI: 10.12005/orms.2020.0030

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In order to improve the accuracy and comprehensiveness of efficiency evaluation of EWMA control chart, product numbers in a quality cycle are proposed to replace sample numbers for economic and statistical evaluation, and a more accurate economic-statistical design model of EWMA control chart is established based on average product length. A numerical example is given to illustrate the main steps of calculating the model with NSGA-Ш.Finally, the economic-statistical design of EWMA chart with this model is compared with several existing design methods. The results show that the performance of economic-statistical design is better than economic design of EWMA chart and statistical design of EWMA chart.

Risk Averting Index-based Investment and Stochastic Linear Quadratic Optimal Control

LI Yuan-de, CHEN Qi-hong

2020, 29(2):  28-39.  DOI: 10.12005/orms.2020.0031

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This paper focuses on the index tracking problem with the investor's risk aversion taken into account. We try to minimize the weighted sum of tracking error and portfolio risk which is assumed to be the accumulated variance of the risk asset in the portfolio process. The main conclusion is that whether it is for continuous or discrete case, finite or infinite time zone, under certain conditions, the optimal control will uniquely exist. In other words, the optimal investment strategy is available by using stochastic optimal control for index-based investment.

Cost Optimization Model of Second-hand Product Considering Extended Renewing Two-phase Warranty

DONG Ke, LUO Yun-peng

2020, 29(2):  40-46.  DOI: 10.12005/orms.2020.0032

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This paper presents a model for second-hand products with an extended two-phase warranty while the definition of life cycle is reexamined. The factors such as product's age changed, extended warranty discount, minimal repair and lost production costs are taken into consideration in this model. It aims to fulfill the customers' expectation of minimizing the total cost rate per unit. Accordingly, free replacement/repair warranty policy and pro-rata replacement warranty policy are offered. As a proof of the model's optimal value, related theoretical explanation is provided. Above all, a case study, including the analysis for the sensitivity of the parameters, verifies the validity of the model. The conclusion can provide decision basis for customers with product maintenance plans.

Integrated Continuous Berth Allocation and Time-variant Quay Crane Assignment under Berth Dredging in Container Terminal

JIAO Xiao-gang, ZHENG Fei-feng, XU Yin-feng, LIU Ming

2020, 29(2):  47-57.  DOI: 10.12005/orms.2020.0033

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To deal with the practical requirement of berth maintenance in container terminal operations, this paper aims to the integrated problem of continuous berth allocation and time-variant quay crane assignment where berth dredging is involved. We develop an integer linear programming model, and then propose three heuristic algorithms to solve the problem. In order to analyze berth dredging influence on terminal operations and validate the model together with the algorithms, extensive numerical experiments are tested for both scenarios with or without berth dredging issues in the integrated berth allocation and quay crane assignment model. The numerical results show that the three heuristic algorithms can produce exact solutions as CPLEX does for all the small-scale instances. For large-scale instances, we make a comparison between the solutions of the three algorithms.

A Decision Making Method for Pythagorean Fuzzy Numbers Based on Generalized WOWA Operator

LI Peng, SHEN Zhi-jie

2020, 29(2):  58-65.  DOI: 10.12005/orms.2020.0034

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This paper mainly studies the multiple criteria decision making problems for Pythagorean numbers. A Pythagorean fuzzy generalized weighted ordered weighted average (PF-GWOWA) operator is proposed. Firstly, the PF-GWOWA operator is proposed. We use three theorems to prove that Pythagorean fuzzy generalized weighted average (PF-GWA) operator, Pythagorean fuzzy weighted ordered weighted average (PF-WOWA) operator and Pythagorean fuzzy weighted average (PF-WA) operator are special cases. Then, according to the model of obtaining comprehensive criteria weights, we aggregate the Pythagorean fuzzy information by the PF-GWOWA operator and use the score function and accurate function to rank the alternatives and choose the best one. Finally, an example is proposed and compared with the traditional method to illustrate the rationality and effectiveness of our proposed method.

Group Emergency Alternative Adaptation Method Oriented Characteristic of Multi-department and Multi-attribute

ZHENG Jing, WANG Ying-ming

2020, 29(2):  66-72.  DOI: 10.12005/orms.2020.0035

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In order to solve the problem of the emergency alternative generation based on case-based reasoning with the characteristic of multi-department and multi-attribute, a new emergency alternative adaptation method based on group decision making is proposed. Firstly, each department generates a case base according to the concerned attributes, and the most similar historical case is obtained according to the retrieval method. The emergency alternative for each department is generated through the emergency alternative adaptation using the belief rule-base. Next, each department evaluates the emergency alternatives. Furthermore, the department weights are determined according to the evaluation information, and the final emergency alternative is generated by integrating the emergency alternatives of the participating departments. Finally, an illustrative example is provided to demonstrate the feasibility and validity of the proposed method.

Study of Loading-unloading Operation at Railway Container Terminal Based on Game Theory

WANG Qing-bin, WANG Cui-ping, XIAO Qin-fei

2020, 29(2):  73-87.  DOI: 10.12005/orms.2020.0036

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Considering the competitive factors between different loading-unloading tasks at the railway container terminal, a method of game theory is used to study the handling resources scheduling and the sequence of operation. A game model is established and a genetic algorithm is designed based on the model. By solving a typical example of the problem, the obtained equilibrium solution is compared with the static optimal solution, and the difference between the work plan considering the competition factor and the optimal operation plan is analyzed. The results show that this method fully considers the fairness of the competition among the loading-unloading tasks under the condition of less influence on the optimal solution, and provides scientific basis for the terminal to determine a more reasonable loading-unloading operation sequence and resource scheduling.

Evolutionary Game Analysis ofthe Supervision Mechanism of New Energy Time-sharingRentalVehicles

WAN Xiao-yu, CHEN Ye-jian

2020, 29(2):  79-98.  DOI: 10.12005/orms.2020.0037

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Presently, new energy time-sharing rental vehicles are in an early stage of development in China, and problems like ineffective operation, security issues and subsidies cheating arise one after another, which have caused great trouble to consumers and the government. In this paper, a three-way dynamic game model among government, enterprises and consumers is constructed and solved based on the evolutionary game theory. The model results are numerically simulated by Python software. Theresearch shows that there are four evolutionary stability results when the key parameters are set in different numerical ranges. Therefore, appropriately increasing the amount of subsidy and punishment, increasing the proportion of compensation coefficient received by consumers, and urging enterprises to reduce operating costs are conducive to the healthy development of the new energy vehicle rental market.The conclusions of the research can work as a theoretical basis and reference for government sectors to make and implement a policy.

Value-at-Risk-based Fuzzy Two-stage Model for Logistics Network Planning and Its Accurate Solution Approach

WANG Ke, YANG Yan, ZHOU Jian

2020, 29(2):  88-107.  DOI: 10.12005/orms.2020.0038

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A fuzzy two-stage programming model with Value-at-Risk(VaR)criterion is proposed for controlling the investment risk in logistics network planning, considering the uncertainty of customer demands and transportation costs. The objective is to minimize the VaR of investment loss. It is proved that the fuzzy two-stage programming model involving regular fuzzy parameters can be transformed into an equivalent deterministic one-stage programming model, thus the infinite-dimensional optimization problem can be converted to a classical finite-dimensional problem, by which the computational complexity of solving the two-stage model is significantly decreased and meanwhile exact solutions can be obtained. Numerical examples with different sizes illustrate the effectiveness of the proposed model and solution approach.

Hybrid Algorithms for the Pickup and Delivery Problem with Time Windows

BIAN Zhan, ZHANG Qian, XU Qi, JIN Zhi-hong

2020, 29(2):  99-115.  DOI: 10.12005/orms.2020.0039

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In order to solve the pickup and delivery problem with time windows, a set partition model is built. A hybrid algorithm CGA which combines the column generation algorithm and heuristic rules is designed to solve the problem. First of all, the main problem and the restricted main problem are constructed by relaxing constraints, and simplex method and branch-bound are used to solve the problem. Second, the sub-problem is constructed with the space network, and algorithms A, B1, B2 based on the modified Dijkstra's algorithm are designed. At last, heuristics are used to solve the nodes overlap problem. In order to verify the validity of the algorithm, an approximate optimal algorithm OPT is further constructed. Based on the CGA, three solving strategies C1, C2 and C3 are proposed to execute the one-way ANOVA. Numerical examples are used to analyze the performance of the algorithm. The analysis result shows that for the small-scale cases with less than 30 customers, the results obtained by CGA and OPT are similar but the CGA has more significant efficiency. For the large-scale cases with up to 600 customers, the CGA can get the result within 20 minutes The result shows that the proposed algorithm is more accurate and efficient. For the different types and sizes of customers, the one-way ANOVA result shows that C1, C2 and C3 are significantly different in the three dimensions of “average travelling cost”, “average number of vehicles” and “average computing time”. Operators can choose the tactics according to the actual demands.

Weight Calculation of Innovative Demands Based on Ideal Point-Vector Projection method

KONG Zao-jie, LI Bin

2020, 29(2):  108-121.  DOI: 10.12005/orms.2020.0040

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Most existing methods for calculating the weights of innovative demands only take one or two angles of the influence from customers, technicians and decision makers into consideration, and there are few methods to consider all the three parties into the process of weights calculation of demands at the same time, which lead to low accuracy and incorrectness of the weights calculation because of the incomplete information. In order to solve this problem, this paper proposes a method based on the Ideal Point-Vector Projection method to calculate the weights of innovative demands, this method integrates the influence of customers, technicians and decision-makers in three dimensions vector space. Calculating the demand category factors, demand technology maturity degree and demand preference degree, and using the Ideal Point-Vector Projection method to acquire the ideal demand vector, we calculate the weights of each innovative demand based on the ideal demand vector. An empirical study of the research and development of car steering wheel is illustrated and proves the effectiveness and feasibility of the proposed method.

Economic Design of EWMA Control Charts with Variable Sampling Intervals under Preventive Maintenance and Quality Loss Functions

XUE Li

2020, 29(2):  116-128.  DOI: 10.12005/orms.2020.0041

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To improve the monitoring efficiency while reducing costs for process control, economic design of exponential weighted moving average(EWMA)control chart with variable sampling intervals(VSI)under preventive maintenance and quality loss functions is discussed in this paper. Firstly, the integrated economic model for combining the preventive maintenance and the economic design of VSI EWMA control chart using quality loss functions is developed. Further, the optimal values of the parameters will be determined such that the expected loss function of unit time in an average cycle process is minimized. Secondly, a calculation example is provided and the genetic algorithms will be used to search for the optimal values of the parameters of the VSI EWMA control chart. Finally, the sensitivity analysis ofthis proposed model is done to find the influence relationship between the model parameters and the design parameters.

Research on Supply Chain Network Equilibrium Model Based on Improved Particle Swarm Optimization

MA Bin, WU Ze-zhong

2020, 29(2):  122-136.  DOI: 10.12005/orms.2020.0042

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The traditional method of supply chain is projection, but it is very complex to calculate the projection. This paper presents an improved particle swarm algorithm to solve the problem of the supply chain network equilibrium. Constantly adjusting learning factor to balance the global exploring ability and the ability of local development of the algorithm improves optimization precision of algorithm. Through four numerical examples, and comparing with the standard particle swarm algorithm, artificial bee colony algorithm, and the particle swarm optimization algorithm with synchronous learning factor, the improved particle swarm optimization algorithm is proved to be effective and superior in solving the supply chain network equilibrium problem. It provides a new method for solving the supply chain network.

Application Research

A Multi Knowledge Points Labeling Method for Test Questions Based on Ensemble Learning

GUO Chong-hui, LV Zheng-da

2020, 29(2):  129-143.  DOI: 10.12005/orms.2020.0043

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Education data mining tasks such as personalized test question recommendation, test question difficulty prediction, learner modeling need answer data and test question labeled with knowledge points. At present, the test question data are labeled manually. Therefore, it is an urgent need to label the knowledge points automatically by utilizing machine learning. In order to label knowledge points to massive test questions, a multi knowledge points labeling method based on ensemble learning is proposed in this paper. Firstly, the problem of labeling knowledge points is formally defined, and the knowledge graph of knowledge points is used as category labels with the help of textbooks. Secondly, the ensemble learning based method is used to train multiple support vector machines as the base classifiers, which are selected for integration with excellent performance , building the multi knowledge points labeling model. Finally, the high school mathematics test questions in the online education platform database are used as the experimental data sets. The method is used to predict the knowledge points of the test questions, and good results have been achieved.

Parameters Estimation and Application of Fast Mean-reverting Stochastic Volatility Model

LI Peng-shi, YANG Jian-hui, LIN Yan

2020, 29(2):  137-143.  DOI: 10.12005/orms.2020.0044

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Under the assumptions that asset price is a geometric Brownian process and the price volatility is constant, Black-Scholes model is an ideal pricing model for European options. Despite the success and popularity of BS model, studies in empirical finance reveal that the implied volatility obtained from financial market data is not a constant but shows the implied volatility “smile” phenomena, thus the assumption of constant volatility is unrealistic. Based on fast mean-reverting stochastic volatility model, this paper investigates the pricing problem of collar option. The pricing formula of the collar option with stochastic volatility is also derived. Based on the implied volatility and historic data obtained from the SPDR S&P 500 ETF option market, two parameters of the fast mean-reverting stochastic volatility model are calibrated. With these calibrated parameters and the pricing formula, the numerical experiment on option price is carried out. The experiment result shows that collar option with stochastic volatility is underpriced compared to option with constant volatility.

A Zero Sum Gains Slacks-based Measure Efficiency Decision-making Method and Its Application

GUO Wen, SUN Tao, ZHU Jian-jun

2020, 29(2):  144-149.  DOI: 10.12005/orms.2020.0045

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On the basis of slacks-based measure(SBM)efficiency decision-making method, we clear the competitiveness relationship among all of the decision-making units(DMU)in the production system which has fixed input(output)elements. Then, we allocate input(output)slacks of SBM inefficiency DMU through using proportional allocation strategy, and establish a zero sum gains SBM(ZSG-SBM) efficiency decision-making method. And then we provide solution method of ZSG-SBM model through analyzing the relationship between the ZSG-SBM model and traditional SBM model. Finally, we verify the advantage of ZSG-SBM model in solving efficiency evaluation and resource allocation decision-making problems by an example.

Analysis and Time Lag Measurement of the Influencing Factors on Universities R&D Based on Grey Incidence Model

LIU Yong, DU Jun-liang, ZHAO Huan-huan

2020, 29(2):  150-156.  DOI: 10.12005/orms.2020.0046

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The “two skin” problem between universities' technology and economic development is generally more prominent, so that how to extract the important factors on R&D performance of universities and measure their time lag has a great significance for generating the “deep knowledge” to guide or assist the decision and promote the transformation of science and technological achievements. According to the Compilation of Science and Technology Statistics of Higher Education" from 2005 to 2015, with respect to the hysteresis and inconsistent development trend of R&D input and output, a novel grey incidence analysis model with time lag is established by using the tangent function, and then it is utilized to analyze the influencing factors and measure their time lags in universities from Jiangsu province. The results show that the influencing factors in each stage have strong influence and effect on the R&D performance, and the trend is decreasing with the extension of the lagging year; the number of year investment talents and the current year expenditure for the university R&D institutions are the important influencing factors of R&D performance in the stage of knowledge output, the R&D full-time talents, and basic research funds and applied research funds are the key factors restricting its performance improvement; while the full time staff and funds of achievement application and technology service are the important influencing factors and bottleneck factors of R&D performance in the process of achievement transformation, respectively.

Research into Salary Incentive Based on University Development Strategy, Teachers' Reasonable Performance Incentives and University Development Achievements

CAO Rong, YU Bin

2020, 29(2):  157-160.  DOI: 10.12005/orms.2020.0047

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Taking teacher's merit payment in eastern colleges and universities as the sample, and based on development strategies of college and universities, this paper analyzes from 3 aspects of teacher's merit payment the influence of development strategies on salary incentives and the matching development strategies with various salary incentives. The analysis result shows that colleges and universities shall take their own development strategies into consideration in choosing incentives of merit payment and make efforts to rationalize the chosen incentives, which is of certain significance in the design of salary incentive system for teachers in college and universities.

Measure on the Extreme Risk Contribution of a Portfolio Based On the Saddle Point Approximation

FAN Qi, QIN Xue-zhi, WANG Lin, SONG Yu

2020, 29(2):  161-165.  DOI: 10.12005/orms.2020.0048

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Against the background of high price fluctuations in today's economic environment, it is significant to analyze the deep reasons for the portfolio volatility by measuring the risk contribution of each asset. Historical data measure method has been widely used in risk contribution which is mainly suitable for the situation of larger data sample and short duration up to now. Generally, the risk contribution in extreme situation is decided by the feature of the tail data. Therefore, it is difficult to make sure of the accuracy of estimation in this case. In this article, we optimize the saddle point approximation to solve the above problem, and make an empirical analysis of these methods by using Chinese stock data. Compared with the traditional methods, the advantages of the saddle point approximation are listed as follows: the distribution function of the portfolio is more concise and the calculation has a higher accuracy and efficiency. Moreover, the stress test results show that the saddle point approximation model has more stability. Therefore, it is likely that the saddle point approximation will be helpful for early warning of risk and the risk prevention for investment portfolio.

The Dynamic Relationship Between the Intraday Absolute Yield and Trading Volume of the CSI 300 Stock Index Futures

WANG Su-sheng, LI Guang-lu, WANG Jun-bo

2020, 29(2):  166-174.  DOI: 10.12005/orms.2020.0049

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The absolute return of the sample with zero mean can be regarded as an unbiased estimator of volatility. Therefore, this paper chooses high frequency data of 20 consecutive trading days to study the dynamic relationship between the absolute return and trading volume of theCSI300 stock index futures.After checking the stability of the sample, the paper uses Granger test to test the causality between the intraday absolute return rate and the volume of stock index futures. The test results show that the volume of all samples is not the Granger cause of the absolute return rate, while the absolute return rate of 15 samples of 20 samples is the Granger cause of the volume.Then we use the vector autoregressive model to estimate the coefficients of 15 models, and analyze the impulse response of the estimated results. It is found that under this high-frequency sampling condition, unlike previous studies, the change of the absolute yield of theCSI300 stock index futures will significantly reduce the volume of trading during the observation period. This paper gives a reasonable explanation for the results.Therefore, in the study of intra-day trading volume and absolute yield of stock index futures, both historical trading volume and yield have an important impact on current trading volume, while absolute yield is only affected by historical absolute yield.

An Evaluation Method and Identification of Independent Director Governance Based on the Advantage Characteristics

YANG Kai, ZHAO Xi-nan, ZHOU Yan

2020, 29(2):  175-183.  DOI: 10.12005/orms.2020.0050

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To analyze the question of independent directors' performance of duties in corporate governance, this paper analyses the performance of independent director and identifies the advantageous characteristics during working in the board of directors, and then a performing evaluation model is proposed from the perspective of various advantages. In this model, first, according to personal idea of configuration, the RepGrid method is applied to check the behavioral features of independent director. Second, the individual advantage parameter and comparative advantages are identified based on the theory of better conforming to nature. Third, combining the independent directors' advantageous parameters and the board's preference, the model is set oriented by the differentiation advantages. Last but not least, a practical example is used to determine the effectiveness and superiority of the method, and some management highlights are put forward to make the independent director execute well.

Study of the Dynamic VaR Forecasting Model of Chinese Stock Market from High Frequency Perspective

CHEN Wang, MA Feng, WEI Yu, LIN Yu

2020, 29(2):  184-194.  DOI: 10.12005/orms.2020.0051

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How to effectively obtain more valuable information from trading data is of vital importance to the financial risk management. However, in the existing studies, the risk measurement method based on low-frequency volatility model has almost reached the limit, but the predictive effect is not robust and the research on high-frequency volatility model is relatively scarce. The question is whether the high-frequency models can extract more valuable information from high-frequency data, which is useful for risk management. To carry out the rolling forecast of out of sample dynamic VaR based on the SSE Composite Index, we establish 12 low-frequency and 9 high-frequency volatility models. The empirical results show that high-frequency volatility models are more robust than low-frequency models and high-frequency models are superior to low-frequency in the most cases. What's more, the risk prediction effects of long and short position are extremely different. As for the long position, high frequency models do well under high risk situations but do poorly in the case of low risk situations, while the short position performs well in all cases.

Price Discovery of the Periodic Auction Mechanism in the Chinese New Three Board

XIANG Jian-kai, WANG Chun-feng, LI Yang, FANG Zhen-ming

2020, 29(2):  195-204.  DOI: 10.12005/orms.2020.0052

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The theory of market microstructure indicates that the transaction mechanism has an important influence on the formation process of asset price. In this paper, we explore how periodic auction affects price discovery process against the backdrop of transaction mechanism reform of the Chinese New Three Board. The key of the periodic auction system lies in the setting of market clearing time interval. We develop a theoretical model to study how clearing frequency affect the liquidity risk, the price discovery efficiency and the uncertainty of asset value considering information friction and Bayesian learning process of informed traders. We find that: (1)Under the condition of perfect information, setting a short market clearing time interval would reduce the liquidity risk of investors and improve the quality of the market when the market scale is larger or the volatility of asset value is higher. (2)Under the condition of imperfect information condition, the optimal clearing frequency depends on the degree of information asymmetry and the ratio of informed traders except for market scale and volatility of asset value. (3)Under the condition of imperfect information condition, setting a short market clearing time interval would reduce the liquidity risk of investors when the volatility of asset value is lower, which is in contrast with the condition of perfect information.

Management Science

A Study on the Difference and Convergence of Total Factor Productivity of the Manufacturing Industry in China ——An Empirical Analysis Based on the Enterprise Micro Data

GUO Chun-na

2020, 29(2):  205-211.  DOI: 10.12005/orms.2020.0053

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Based on the enterprise micro data of Annual Survey of Industrial Firms in China, this paper studies TFPs of Manufacturing Industry and their difference and convergence among regions in China in term of OP model and convergence method. The following conclusions are made. First, on the whole, the overall TFP growth rate is 2.36% in the period from 2002 to 2011 while it is only-2.14% in the period from 2008 to 2011. Second, the TFPs are significantly different according to the regions, that is, the eastern coastal areas have relatively low rates of TFPs while the central and western regions have high ones. Third, the analysis of convergence indicates that there is neitherβconvergence norσconvergence among different regions, but there is club convergence among eastern, middle and western regions respectively. Finally, on the whole, capital growth rate and R&D have a significant positive impact on the growth of TFPs while the ratio of dependence on foreign trade is not significant.

Multi-Objective Planning Model and Algorithm for Coordinative Production Considering Individual Interests in the Multi-factory Environment

JING Yi, LI Qin

2020, 29(2):  212-218.  DOI: 10.12005/orms.2020.0054

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For the distributed system consisting of multiple factories, the multi-objective planning model for coordinative production is established considering the individual interests of different factories. In this model, the maximization of overall profit is designed as the first optimization objective. Meanwhile, based on the Adams's fairness theory, adopting the deviation coefficient method, the minimization of individual profit balance deviation is designed as the second optimization objective. According to the characteristics of model structure, the corresponding solving process is designed based on Fast Elitist Non-dominated Sorting Genetic Algorithm(NSGA-II).Finally, the multi-objective multi-factory coordinative production planning model and solution method designed in this paper are applied to a multi-factory coordinative production system of automobile engines. The numerical example shows that the multi-objective planning model and the solution method designed in this paper can not only coordinate the production, inventory and transportation activities of each factory from the perspective of network integration, but also achieve the minimization of the non-uniformity between overall interests and individual ones, effectively protecting the individual interests of each factory and the overall benefits of the system.

Research on the Supply of Pension Service Market Based on Government Subsidy

GUO Qian, WANG Xiao-li

2020, 29(2):  219-228.  DOI: 10.12005/orms.2020.0055

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With the acceleration of the aging process in China, the effective supply of the elderly service is the focus of government and scholars. Considering government subsidies, we introduce the alternative factor endowment service, build endowment service market supply dynamic game model between private pension institution and public pension institution, and analyze the influence of subsidy ways for pension services balanced supply and the influence degree of government subsidy on the optimal supply decisions of the two pension service institutions through the subsidy effect. The results show that government financial incentives for private pension agency can increase the pension services market supply. Compared with operating subsidies, multiplier effect of construction subsidies is more obvious; The financial subsidy reduces the construction cost and investment risk of private pension institutions, stimulates the enthusiasm of social capital, and the increase of private pension service institutions is larger than that of public pension service institutions. Under the constraint of fiscal budget, choosing appropriate fiscal subsidy mode can improve the allocation efficiency of financial resources, increase the effective supply of the pension service market, and alleviate the financial pressure of pension service.

Overview

Operations Research 1996~2017: A Retrospective Statistical Analysis

Hong-tao WANG Hong-tao, ZHANG Xiang, WANG Ke

2020, 29(2):  229-239.  DOI: 10.12005/orms.2019.0056

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Operations Research(OR)is a top journal in the field of operations research and management science. We conduct statistical analysis of its articles, analyzes the mainstream research institutions in the field of international operations science and the influence of cooperation, and explores current research hot topics and discipline development trends, which play a very important guiding role in the development of China's operations research discipline. Based on the statistical analysis of all journals published in the WOS core database from 1996 to 2017, the following conclusions have been drawn: In recent years, Chinese scholars have steadily increased the number of articles issued, which indicates a significant advance in the level of research in China's operational research disciplines, but its influence remains to be intensified. Institutional cooperation, international cooperation will contribute to the increase in the number of articles cited; cited analysis shows that flexible manufacturing (process flexibility and efficiency), the application of nested Logit model, network revenue management and other seven research directions are current and persistent research hotspot in the field of operational research.