Table of Content

25 September 2017, Volume 26 Issue 9

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Theory Analysis and Methodology Study

Intuitionistic Fuzzy multi-Attribute Group Decision-making Method Based on Evidential Reasoning

DAI Wen-feng, ZHONG Qiu-yan, HE Dong-dong

2017, 26(9):  1-6.  DOI: 10.12005/orms.2017.0203

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This paper proposes a new decision-making method for the problem of multi-attribute group decision making, in which attribute values are intuitionistic fuzzy numbers. At first, the synthetic weights of attributes and experts are computed by the intuitionistic fuzzy entropy according to the subjective and objective factors. Then, an intuitionistic fuzzy information fusion method based on evidential reasoning is proposed. This method can avoid information loss caused by the membership degree being zero and make up for the shortcomings of the existing fuzzy information fusion methods. Based on this, the evaluation information is aggregated and alternatives are ranked according to the relative closeness coefficients of each alternative to the ideal alternative. Finally, a numerical example is presented to demonstrate the effectiveness of the proposed method.

A Multi-Attribute Decision-Making Method in Intuitionistic Fuzzy Set based on Vertical Projection Distance and IFE

CHEN Wei, LI Jin-qiu, YANG Zao-li

2017, 26(9):  7-12.  DOI: 10.12005/orms.2017.0204

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This paper presented a new method for intuitionistic fuzzy multi-attribute decision-making problems with unknown attribute weight information based on vertical projection distance and intuitionistic fuzzy entropy(IFE). In the proposed model, we substitute vertical projection distance for relative Euclidean distance in traditional TOPSIS, which has obvious drawback on reverse order, to develop a new ranking alternatives rule for intuitionistic fuzzy multi-attribute decision-making; we construct a nonlinear programming model based on minimizing vertical projection distance and intuitionistic fuzzy entropy(IFE), which combines subjective information preferences with objective ones to determine the attribute weight, and obtain the optimal alternative; Finally, an numerical example is given to illustrate the efficiency and applicability of the proposed method.

Interval-valued Hesitant Fuzzy Bonferroni Mean Operators and Their Application to Multiple Attribute Decision Making

YU Qian, HOU Fu-jun, DU Yu-qin, ZhAI Yu-bing

2017, 26(9):  13-20.  DOI: 10.12005/orms.2017.0205

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A multiple attribute decision making method based on interval dependent fuzzy Bonferroni mean operator is proposed to solve the multiple attribute decision making problems when the interaction between input variables and expert evaluation value is interval hesitation fuzzy information. Considering that the Bonferroni mean(BM)operator can well reflect the influence of the input variables, we first propose two new integrated operators with the evaluation value as the interval hesitation fuzzy information environment, namely, the interval bonus fuzzy Bonferroni mean(IVHFBM)operator and interval hesitation fuzzy geometry Bonferroni mean(IVHFGBM)operator. And we discussed some of its related characteristics. At the same time, the Bonferroni mean(IVHFWBM)operator and the interval bonus fuzzy weighted geometric Bonferroni mean (IVHFWGBM) operator are defined based on the case where the input variables will have different degrees of importance. A multiple attribute decision making method based on IVHFWBM operator and IVHFWGBM operator is proposed to solve the decision problem of interval hesitation fuzzy set. Finally, an example is given to illustrate the application of these operators in interval hesitation fuzzy multiple attribute decision making. The results show that the method is feasible and effective.

Emergency Medical Service Station Robust Location Model and Algorithm Under Demand Uncertainty

PENG Chun, LI Jin-lin, RAN Lun, WANG Shan-shan

2017, 26(9):  21-28.  DOI: 10.12005/orms.2017.0206

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After large-scale emergent incidents, it is particularly urgent to start emergency relief network quickly and locate the emergency medical service stations. We incorporate demand uncertainty, introduce three uncertain level parameters, construct four types of demand uncertainty sets, and propose robust EMSS location models respectively. Then, we derive their tractable robust counterparts, and employ branch-cut algorithm to solve the problems. Finally, we present computational results, and perform sensitivity analysis. Numerical results show that, among four robust location models, robust EMSS location model with ellipsoid uncertainty set opens fewer EMSSs, and the total cost is smaller. According to the uncertainty of risk preference, decision-makers usually choose optimal budget uncertainty and demand disturbance proportion, so as to minimize the total cost.

An Improved Differential Evaluation Algorithm for a Bin Packing Problem with Concave Costs of Bin Utilization

WANG Gong-shu, ZHANG Xin-bang, XING Hang, LI Gui-dong

2017, 26(9):  29-36.  DOI: 10.12005/orms.2017.0207

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This paper studies a novel bin-packing problem that is widely encountered in logistics operations. The main novelty can be characterized by the fact that the cost of a bin is a concave function of the utilization of the bin. To solve the problem, an improved differential evaluation algorithm using group-based encoding scheme is proposed such that the shortcomings of enlarging search space that the conventional real and integer encoding methods may encounter are avoided. To comply with the group-based encoding scheme, we design new and tailored crossover and mutation operators so as to promote the transmission of the excellent genes. In order to further improve the performance of the algorithm, an adaptive local search strategy that uses items rearrangement as neighbors is embedded in solution framework to enhance the intensification ability. We test our algorithm on instances collected from an existing article over different concave cost functions. The computational results show that the proposed algorithm outperforms the BFD heuristics, and improves much more than the genetic algorithm.

One-way Channel Ship Inbound Order and Berth Allocation Collaborative Optimization

ZHENG Hong-xing, XU Hai-dong, LIU Bao-li, CAO Hong-lei

2017, 26(9):  37-45.  DOI: 10.12005/orms.2017.0208

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In order to improve the service level of the one-way channel discrete berth port, this paper studies the ship inbound order and berth allocation collaborative optimization. In the planning period, considering the practical constraints of ships entering port and berth operation, a mixed integer programming model is proposed to minimize the sum of all ships anchorage and berthing waiting cost, the demurrage cost and deviation berth cost. Then the harmony algorithm embedded Taboo Search Algorithm is designed to solve the problem. The results from numerical experiments show each ship arrival order and berthing spaces, and furthermore, the effectiveness of the model and algorithm is verified by contrast with an individual optimization scheme and the solution effect analysis of numerical changes in the size of cases.The influence of the change of the time setting on the operating cost is analyzed,determining the optimal length of time setting under different vessels scales, which can provide the reference for the time setting of the one-way channel port.

Solving Permutation Flow-Shop Scheduling Problem by Central Force Optimization Algorithm

LIU Yong, MA Liang

2017, 26(9):  46-51.  DOI: 10.12005/orms.2017.0209

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The existing intelligent optimization algorithms for permutation flow-shop scheduling problem are all stochastic optimization methods. One problem with these approaches is that they have poor solution stability. In this paper, a method based on central force optimization algorithm which is a deterministic intelligent optimization algorithm is proposed to resolve this problem. The basic algorithm depends upon the choice of the initial solutions. To deal with this problem, low-discrepancy sequences are used to generate initial solutions to improve the quality of initial solutions. The acceleration and position equations are employed to update the solutions. A sorting method to swap two positions in a solution is used to conduct local searches, to enhance the performance of the algorithm. The benchmarks are used to perform numerical experiments. The presented algorithm is compared with basic central force optimization algorithm, NEH heuristic algorithm, particle swarm optimization algorithm, and firefly algorithm. The results demonstrate that the proposed method not only has better solution stability but also higher accuracy. The presented approach provides a feasible and effective way to solve the permutation flow-shop scheduling problem.

Multi-objective Evolutionary Algorithm Optimization of Stochastic Mixed-model U-shaped Disassembly Line Balancing and Sequencing Problem

GU Xin-jun, GUO Xiu-ping

2017, 26(9):  52-61.  DOI: 10.12005/orms.2017.0210

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To solve the mixed model U-shaped disassembly line balancing and sequencing problem with stochastic task times, a mathematical model is established aiming at minimizing mean line idle rates, removing hazardous and high-demand parts as early as possible and minimizing the mean number of part removal direction changes. Besides, a hybrid multi-objective evolutionary algorithm based on decomposition and dynamic neighborhood search method(HMOEA/D)is proposed to solve the problem. In HMOEA/D, a flexible tasks assignment strategy, dynamic neighborhood structure and dynamic weight vector adjustment are adopted to ensure the solutions’ feasibility and the distribution of the non-dominated set. Finally, the algorithm is tested on benchmark instances generated by using Design of Experiment(DOE)techniques. Experimental results show that HMOEA/D can get an approximation set closer to the Pareto optimal front and distributed better when compared to other algorithms.

Research on the Problem of the Tourism Route Planning By Optimization of Partitioning Block and Layer

ZHONG Yi-hua, LUO Shi-ming

2017, 26(9):  62-67.  DOI: 10.12005/orms.2017.0211

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With the problem that route planning of tourism determines success or failure for travel of tourists by self-driving, the network optimization problem of tourism route planning was solved by using the idea of optimization of partitioning block and layer. The weighted graphs of partitioned network were constructed by using the idea of weighted graph and the nearest neighbor clustering algorithm to divide the scenic spots, and an improved TSP optimal model was established to plan the tourist routes of the scenic spot in the block for self-driving travel,which considers the travel time and driving time as well as visiting time during every time travel process. Then, an improved MTSP optimal model was established by treating each block as a note, treating the travel time of the block as one of the time weights, moreover tourist routes among blocks for self-driving travel were planned by using the simulated annealing algorithm. Next, the one-dimensional Bin Packing(BP)model to solve the minimum number of total tourism years was established through the idea of analogy one-dimensional Bin Packing problem, and whose minimum value was obtained by using cross filling algorithm. Finally, the optimal tourist routes that subjects to multiple constraints were planned for a travel enthusiast by self-driving in Xi’an City who travels through 201 5A level scenic spots in china with applying the proposed method in this thesis.

Evolutionary Game Analysis on Impacts of Government Regulation on Enterprises’ Environmental Innovation Mode Selection

XU Jian-zhong, GUAN Jun, ZHU Xiao-ya

2017, 26(9):  68-77.  DOI: 10.12005/orms.2017.0212

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In order to gain advantages in competition, enterprises should select a rational environmental innovation mode under environmental regulation. Based on the assumption that enterprises’ products are substitutable and there exist differences between different environmental innovation modes, an evolutionary game model is established which explains the effects of governmental environmental innovation investment subsidies and carbon tax on the selection of enterprises’ environmental innovation mode. Besides, a theoretical and numerical simulation analysis is carried on concerning the evolution path, stable equilibrium strategy and the influence mechanism. The results show that enterprise groups will evolve to an “ideal state” of all adoption environmental breakthrough innovation mode only when they can obtain excess returns under environmental regulation. In addition, both the governmental environmental innovation investment subsidies and carbon tax can encourage enterprises in carrying out environmental innovation activities and can quicken enterprises’ evolution to the environmental breakthrough innovation mode. Moreover, carbon tax should be controlled in a certain range to maximize its incentive effect while its effect is significant.

Application Research

Outpatient Scheduling for Multiple Examinations

LIU Yang, GENG Na

2017, 26(9):  78-87.  DOI: 10.12005/orms.2017.0213

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Timely examinations are important for patients to be properly diagnosed and treated. Different urgency levels of patients, different requirement of examinations, and patients’ behaviors, for example, no-shows, make patient scheduling difficult to solve. To deal with this problem, this paper starts from two different examinations, two urgency levels, patients’ no-shows and physicians’ overtime, and proposes a discount-cost Markov Decision Process(MDP) with the objective to maximize the expected revenue from examining patients and minimize the overtime penalty. Due to the complexity of the MDP model, it is difficult to analyze structural properties of the optimal control policies. Therefore, numerical results of MDP are solved. Based on the observed structural properties of the numerical optimal control policies, this paper proposes two parameterized heuristics for patient scheduling, where the parameters are improved by using Genetic Algorithm. Numerical experiments compare the optimal control policy, the two heuristics, and the First-Come-First-Serve(FCFS)rule. The numerical results show that the performance of the proposed heuristics is within 10% of deviation from the optimal control policy. When the workload of the system is high, the proposed heuristics are much better than FCFS.

Earned Value Management of IT Project Based on Vague Sets Theory

CUI Chun-sheng, YUAN Rui-ping, LIU Yong-sheng

2017, 26(9):  88-93.  DOI: 10.12005/orms.2017.0214

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Earned value management is a management method widely used in project management. The control factor of quality management is discussed in this paper. Based on the uncertainty factors in the quality management, Vague sets theory is used to describe the uncertain factors in the process of project implementation. Meanwhile, standard quality situation of each work package is expressed by Vague value. With the basic operation rules of Vague values, the project quality standard of monitoring points is obtained. Then, the new formula of earned value is gotten. The research results, on the one hand, enrich the connotation of earned value management and improve its adaptability, on the other hand also extend the application space of Vague sets.

Hedonic Price Model Analysis of Factors Contributing to Coastal Park Admission in Dalian

ZHU Jia-wei, WANG Er-da, SUN Wen-zhang

2017, 26(9):  94-104.  DOI: 10.12005/orms.2017.0215

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A hedonic price model is applied in this paper on contributions of natural environmental attributes and recreation activity attributes of coastal parks to the admission price in Dalian. With a panel data analysis of 29 parks during 2010 to 2014, regression results indicate that natural environmental attributes have statistically significant influence (p≤0.10) on the park admission prices except for the sand. Furthermore, most natural environmental attributes have a positive influence with a change leading to the ticket price increase. However, temperature and rainfall impact negatively. Compared with natural environmental attributes, recreation activities existing on sites have a relatively weak influence on the admission price due to the one-ticket price in coastal parks, and yet some recreation activities still have significant influence on the admission price such as aquarium, sea-animal shows and sightseeing tour etc., In addition, the park congestion leads to the negative effect on the marginal willingness to pay and Chinese park’s A-level ranking reveals a positive effect on the park’s marginal willingness to pay. It also provides the empirical analysis and valuable information on park and local policy management such as tourism carrying capacity, environment conservation and admission price settings.

Invulnerability Simulation Analysis of Urban Public Transit Compound System

SHEN Li, XIANG Yang, WANG Zhou-quan, ZHANG Tong, JI Xiao-hui

2017, 26(9):  105-112.  DOI: 10.12005/orms.2017.0216

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Based on the complex network theory, the topological characteristics and invulnerability of urban public transit compound network and its sub-networks are analyzed. The simulation results indicate that subway-bus compound network of Chengdu city and its sub-networks are scale-free and small-world networks, which show robustness to random attack and vulnerability to intentional attack with topological structures described in space L& , and the invulnerability under node attack is lower than that under edge attack. Meanwhile, the invulnerability of subway-bus compound network is higher than both the subway network and bus transit network.

Incentive Structures and Effects of Tournament Incorporating Heterogeneity of Preferences

WEI Guang-xing, TANG Yao

2017, 26(9):  113-126.  DOI: 10.12005/orms.2017.0217

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The tournament incorporating psychological preferences has become a research focus. But it ignores the heterogeneity of preferences. This paper studies the separating and the pooling tournament and compares the incentive structures and effects in behavioral game theory, which are based on grouping by the types of preferences. It is found that on the side of incentive structures, both the prize intensity and the guaranteed intensity of the separating tournament among the selfish agents are always the biggest, while unless the extent of heterogeneity is very significant those of separating tournament among the agents preferring fairness are the smallest, and on the side of incentive effects, the agents preferring fairness can only gain the reservation utility in both the pooling and the separating tournament, while the selfish agents gain more utility in the separating although in the pooling tournament they can only gain the reservation utility too, and the principal can get more profits in the separating tournament. Therefore, it is necessary for promoting the incentive efficiency of tournament to take the heterogeneity of preferences into account, screen the preferences of employees, and make suitable incentive structures.

Comparative Analysis of Price Discovery in Three SSE 50 Index Markets: the Index Futures, ETF and ETF Options Markets

WANG Su-sheng, XU Tong-tong, WANG Jun-bo, YU Zhen

2017, 26(9):  127-136.  DOI: 10.12005/orms.2017.0218

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This study investigates the price discovery function in Shanghai 50 index markets: the index futures, ETF and ETF options markets. Put-call parity is applied to calculate the implied spot price of ETF options. Using 5 minutes high frequency matched synchronous data, Granger causality tests, generalized impulse response, Johannsen cointegration tests and vector error correction model are employed to analyse the lead-lag relationship of spots and derivatives. The results indicate that the three price series are a cointegrated system with one long-run stochastic trend, and stock index futures price leads other market at least 5 minutes. When the contribution of price discovery is calculated by using the generalized information sharing model and permanent transitory model, it is found that the futures market serves the dominant price discovery function in the long term. However, the ETF market serves the dominant during the boom period, and the ETF options market serves the dominant during the crash period.

A Credit Rating Model of Microfinance Loans for Small Private Business Based on PROMETHEE-II and Its Empirical Study

SHI Bao-feng, LIU Feng, WANG Jian-jun, CHI Guo-tai

2017, 26(9):  137-147.  DOI: 10.12005/orms.2017.0219

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Until the end of year 2014, the number of privately-owned business had reached more than 49 million, and individual private business had absorbed 250 million social workers in China. Due to distribution sparsity and imperfect financial information of Chinese small private businesses, the credit rating system for small private business badly demands improvement. In this study, the credit rating index system of microfinance loans for small private business is established combining correlation analysis and significance discriminant. And then, a credit rating model of microfinance loans for small private business based on PROMETHEE-II and cluster analysis arithmetic is established using the data of 2157 customers in a Chinese national commercial bank. The contribution of this study is three-folded. Firstly, by introducing the method of PROMETHEE-II into credit rating of microfinance loans for small private business, a credit rating model based on PROMETHEE-II is constructed. Using the proposed model the net flow credit score Φ(a)for the small private business a is computed to reflect the impact of relative importance of the small private business a to the rest businesses and interaction among indicators on evaluation results. The trade-off of evaluation indicators which could seriously affect the reliability of results could be overcome. Secondly, by K-W non-parameter test of credit rating results, which are obtained from R cluster analysis, significant difference in the credit scoring values as well as credit characteristic difference of businesses in various levels could be guaranteed. The subjective determination of credit scoring interval and threshold of default probability could be eliminated. Thirdly, the empirical results show that the order of importance affecting the credit risk of microfinance loans for small private business is as follows: X₃ capacity of repaymentX₁ basic information X₆ microenvironment X₅ capacity of operation X₂ guarantee and joint guarantee X₄ capacity of profitability.

Modeling Risk Spillover Effect of the Financial Market Using R-vine-copula-CoVaR Model

LIN Yu, LI Fu-xing, CHEN Zhan, WANG Wei

2017, 26(9):  148-156.  DOI: 10.12005/orms.2017.0220

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In order to tap the direction and intensity of risk spillover between the international financial markets and China’s, in this paper, the jumps and other typical facts of single market return is primarily captured by ARJI-GARCH model; then the R-vine optimized by the maximum spanning tree algorithm is used to depicts the complex dependency structure of multi-dimensional financial assets; Finally, the risk spillover effects between the international crude oil market, the international gold market, the US stock market, Chinese stocks market and foreign exchange markets is measured by R-vine-copula-CoVaR model. The empirical results show that, the risk spillover effect between different markets is bidirectional, but the degrees vary widely, the international gold market is the largest source of risk spillover, the negative risk spillovers exist in China’s foreign exchange market to the stock market and the international gold market; the bidirectional risk spillover effect between different markets is asymmetric with the spillover effect of international crude oil market and gold market is much larger than that of Chinese stock market and foreign exchange market; The Rosenb-Latt test show that risk spillover measured by CoVaR based on R-vine is more flexible and effective; the back testing results show that the R-vine-copula-CoVaR model can effectively measure the risk spillover effects of international financial markets to China's financial markets, while the CoVaR measure of China’s financial market risk spillover maybe overvalued.

Management Science

Knowledge Sharing and Indirect Reciprocity: Research Based on Computational Experiments

LIN Run-hui, MI Jie

2017, 26(9):  157-165.  DOI: 10.12005/orms.2017.0221

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The return of knowledge sharing behaviors often comes from third-party rather than recipients, research of knowledge sharing in direct reciprocity perspective are not insufficient to explain this kind of phenomenon. Adopting the computational experiments based on multi-agent modeling, this study builds a model of indirect reciprocity and knowledge sharing of large teams by giving agents ability to memory information, make decision and communicate. The results show that, due to the existence of discriminators, even unconditional sharers become absolute the majority, hiders are unable to invade the group.This phenomena mean that indirect reciprocity plays a great role in binding widespread knowledge sharing behaviors. The hiders and discriminators will coexist at low level of trust climate in organization, but knowledge sharing behaviors of agents do not appear. Even if only a few individuals can observe knowledge sharing behaviors of colleagues around them, as long as reputation can spread effectively, indirect reciprocity can promote the knowledge sharing behaviors.

Analysis of Influence Mechanism of Industrial Cluster on Enterprise Performance Based on System Dynamics Model

YU Hai-ying, JIANG Ming-hui

2017, 26(9):  166-175.  DOI: 10.12005/orms.2017.0222

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This paper studies the influence mechanism of industry cluster on enterprise performance based on system dynamics. First, the paper discusses the influence from external environment and resources, development of scale and the ability of scientific research and innovation on firm performance by using system causality diagram. On the basis of this, the whole process dynamic analysis of the influence of industrial cluster on enterprise performance is carried out and takes Shanghai pharmaceutical manufacturing industry cluster as an example to make an empirical study. By using Vensim simulation software, the paper discusses the influence mechanism of positive and negative feedback loop in detail. The results show that the external resources environment of industrial clusters, the development scale of industrial clusters and the scientific research innovation ability of industrial clusters have positive impacts on the development of enterprises in the cluster. Enterprises and the government can increase investment in scientific research, improve the external environment of industry cluster, and expand the scale of the industrial cluster to improve enterprise performance which also promotes the sustainable development of enterprises in the industrial cluster.

Empirical Study on the Content Personalization Dimension of Smart Connected Products

LI Tao-Fen, GUO Peng, YANG Shui-Li

2017, 26(9):  176-182.  DOI: 10.12005/orms.2017.0223

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On the basis of literature review and depth interview, twenty-eight content personalization measurement items of smart connected products are extracted. Then through the questionnaire collected data, the dimensions of content personalization and user perception of each dimension are empirical research by used the methods of factor analysis and regression analysis. The research results indicate that the content personalization of smart connected products is consists of five dimensions, which are content recommendation, content customization, content optimization, content extension and content security. Among these factors, the most significant one is content customization, followed by content optimization, content recommendation, content extension and content security.

The Effect of Dynamic Capabilities on the Synergy of Ambidextrous Innovation: the Moderating Effect of Environmental-competitiveness

LI De-qiang, PENG Can, XI Lei

2017, 26(9):  183-192.  DOI: 10.12005/orms.2017.0224

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The synergy of ambidextrous innovation and its antecedents were the important issues that must be considered when the enterprise executed the ambidextrous innovation .And they were also the scholars research frontiers at home and abroad. Firstly, through literature reviews and theoretical analysis, the study explores the relationships between the dynamic capability and ambidextrous innovation synergy and the moderating effect of environmental competitive on these relationships. Then hypotheses and conceptual models are proposed. Secondly, through surveys and statistical analysis, assumptions and conceptual model on the above were empirical tested. Test results showed that: dynamic capability and balance dimension of ambidexterity, combined dimension of ambidexterity and ambidextrous innovation synergy are positively correlated ,dynamic restructuring in transition ability dimensions and balance dimension of ambidexterity, combined dimension of ambidexterity are positively correlated, environment-competitiveness in the dynamic capability and ambidextrous innovation synergy, dynamic ability and balance dimension of ambidexterity plays a positive role in this relationship.

Decision-making and Judgment on the Reverse Logistics Enterprise ——Based on Main Factor TOPSIS and Super-DEA Efficiency Analysis

XIAO Qian-wen, ZHANG Feng-rong, CHEN Ming

2017, 26(9):  193-199.  DOI: 10.12005/orms.2017.0225

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The performance of third-party reverse logistics enterprise is not only concerned about the market competition ability of both sides of supply and demand enterprise under the condition of economic globalization and shortage of resources, but also concerned about the level of environmental social responsibility management. As a separate multi-objectives decision making method, TOPSIS had successfully applied in many professional fields. This paper uses a combination assessment method of main factor analysis and TOPSIS, and establishes the main Factor TOPSIS Analysis model in decision-making on the performance of reverse logistics enterprise with an empirical example, meanwhile, using DEA super efficiency model to analyze operational efficiency of the reverse logistics enterprises and the relative efficiency determination. The evaluation results indicated that the operational efficiency of the overall sample of reverse logistics enterprises is higher, but the efficiency of the reverse logistics enterprises exist different problems, according to the results to find the need to improve.