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30 October 2023, Volume 26 Issue 5 Previous Issue    Next Issue

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System Analysis & Management Decision

Impact of Cost Sharing on Manufacturer Channel Encroachment Strategies in Green Supply Chains GUO Qiang, XU Changhao, NIE Jiajia 2023, 26 (5):  1-10.  doi: 10.3969/j.issn.1007-7375.2023.05.001 Abstract ( 1008 )   HTML ( 410 )   PDF (1006KB) ( 1287 )   Save This paper studies the channel encroachment of manufacturers under the cost sharing strategy of retailers in green supply chains. Game models under different strategy combinations are established to obtain equilibrium solutions of the models. In addition, the equilibrium strategies of both sides and their influences are analyzed. It is found that retailers will not adopt cost sharing strategies in the case of manufacturer channel encroachment, and the profits of retailers are always damaged by manufacturer channel encroachment. When manufacturers do not engage in channel encroachment, whether retailers adopt cost sharing strategies is related to their proportion of cost sharing. Manufacturers always choose channel encroachment when the fixed direct selling cost is low, and give up channel encroachment otherwise. However, when the fixed direct selling cost is moderate, the encroachment strategy of manufacturers is dependent on whether retailers adopt cost sharing strategies. Manufacturers may abandon channel encroachment to enable retailers to share the cost, and then, a win-win situation is achieved. Expansion analysis show that in the case of retailers providing cost sharing contracts, the profits of manufacturers and retailers are improved when the fixed direct selling cost is moderate, where a "triple win" of manufacturers, retailers and product green levels may be realized. References | Related Articles | Metrics

Optimal Pricing Strategies on Bilateral Platforms for Rural Terminal Logistics Distribution DING Xuefeng, WAN Yue 2023, 26 (5):  11-18.  doi: 10.3969/j.issn.1007-7375.2023.05.002 Abstract ( 835 )   HTML ( 764 )   PDF (588KB) ( 996 )   Save This paper proposes a two-part platform pricing model with a mix of membership and transaction prices considering that bilateral platforms of rural logistics have the characteristics of network externality. Mathematical analysis methods are applied to obtain the optimal price strategy under two conditions: the same number of consumer orders and different patience between consumers and platforms. Results show that in a two-part pricing strategy with the same number of orders, consumers can achieve a combination between fixed membership prices and unit transaction prices, as long as there is a certain quantity relationship between the two prices, the optimal profit of the platform is not affected; platforms can adopt flexible and diverse pricing strategies based on different settlement time nodes of membership and transaction prices, including “collect first, return later” or “subsidize first, offset later” pricing strategies, to effectively achieve consumer order stability; when the opportunity cost of capital for consumers and the platform is different, the platform can provide different price strategies to achieve profit maximation based on different degrees of patience. References | Related Articles | Metrics

Effects of Supplier Encroachment on Anti-counterfeiting Governance of Platform Supply Chains ZHANG Zijian, JIN Tian 2023, 26 (5):  19-28.  doi: 10.3969/j.issn.1007-7375.2023.05.003 Abstract ( 872 )   HTML ( 357 )   PDF (1254KB) ( 963 )   Save In order to study the impact of supplier encroachment on product anti-counterfeiting governance in online platform sales, a Stackelberg game model is established to analyze and compare the anti-counterfeiting governance decisions of online platforms with and without supplier encroachment. Results show that there exists a range of commission ratios such that supplier encroachment promotes the strength of anti-counterfeiting governance of a platform. In addition, the profits of resale mode suppliers and platform providers before and after the establishment of the anti-counterfeiting mechanism mainly depend on the influence of the penetration rate of counterfeit goods and the impact of quality differences. The anti-counterfeiting credibility of suppliers in establishing anti-counterfeiting mechanisms is affected by the ratio of platform rent and the proportion of resale modes in the market with supplier encroachment. Also, the anti-counterfeiting credibility is inversely proportional to the platform commission ratio and the proportion of the resale modes. Furthermore, choosing to establish an anti-counterfeiting mechanism can increase the total profit of a supply chain under certain conditions. References | Related Articles | Metrics

A Study on Revenue-sharing Contracts Considering Customer Regret Psychology KANG Huaifei, GUAN Zhenzhong, FENG Guifang 2023, 26 (5):  29-35,68.  doi: 10.3969/j.issn.1007-7375.2023.05.004 Abstract ( 863 )   HTML ( 701 )   PDF (910KB) ( 992 )   Save This paper considers a three-level supply chain consisting of a supplier, a retailer and consumers. Based on the rational expectation equilibrium hypothesis and backward induction, we first analyze the retailer's pricing and inventory decisions, and then discuss revenue-sharing contracts. Results show that, the retailer should adopt the quantity commitment policy to increase profits, and revenue-sharing contracts can increase the credibility of quantity commitment and coordinate the supply chain. However, different from traditional conclusions, the optimal wholesale price may not be necessarily lower than product costs. Moreover, a revenue-sharing contract is effective only when the ratio of bargaining power between the retailer and the supplier reaches a certain threshold. The cooperation willingness of the retailer within the effective interval can be divided into high, medium and low types. Numerical experiments show that the effective interval of a revenue-sharing contract expands with the increase of consumer regret for stockout and narrows with the increase of consumer regret for high prices. References | Related Articles | Metrics

Emergency Operation Decisions of Dual-channel Supply Chains Based on Business Interruption Insurance LI Xinjun, LIU Chunmeng, CAO Yongzhi 2023, 26 (5):  36-47,88.  doi: 10.3969/j.issn.1007-7375.2023.05.005 Abstract ( 769 )   HTML ( 700 )   PDF (1386KB) ( 871 )   Save Due to the frequent occurrence of emergencies such as epidemics and earthquakes, business interruption insurance is often used as an emergency management measure to transfer risks. Based on business interruption insurance, a decision optimization model of insuring and pricing for dual-channel supply chains is built with suppliers buying insurance first and retailers following pricing. An effective revenue-sharing contract for coordination is designed, and extended to differential pricing between suppliers and retailers for online direct sales and offline retail. Results show that with business interruption insurance, the insurance compensation offsets the impact of penalty and shortage costs on price increases, so that both suppliers and retailers tend to reduce prices for promotion to improve their own profits. When the proportion of online demand is larger and the premium rate is smaller, the willingness of suppliers to insure is stronger; with the increase of the proportion of offline demand, the risk transfer effect of purchasing insurance on suppliers becomes weak, and the risk transfer effect on retailers becomes strong. When the cross-price elasticity is large, retailers prefer differential pricing. References | Related Articles | Metrics

A Supply Chain Network Equilibrium Model Considering Labor Flowing Constraints CHEN Zhaobo, WANG Xin, TIAN Chunying 2023, 26 (5):  48-58.  doi: 10.3969/j.issn.1007-7375.2023.05.006 Abstract ( 799 )   HTML ( 360 )   PDF (1562KB) ( 917 )   Save Labor constraints caused by COVID-19 has produced enormous capacity pressure on labor-intensive enterprise. Using shared employees is a method to relieve capacity pressure of enterprises during the COVID-19 pandemic. For a supply chain network system consisting of several competing heterogeneous supply chains, a variational inequality approach is used to develop an equilibrium model of a supply chain network considering labor flowing constraints. Euler algorithm is used to solve the problem, and the impact of labor resources on the equilibrium decision of a supply chain network is analyzed. Furthermore, the impact of "shared employees" on the efficiency of supply chain operation is also discussed. Results show that insufficient labor resources may reduce the production and profits of a supply chain; "shared employees" can help a supply chain better allocate limited labor according to its industrial structure and demand; in some cases, "shared employees" may reduce the operational efficiency of a supply chain. References | Related Articles | Metrics

Interactive Coordination Measures in a Dual-channel Supply Chain Considering the Impact of Preferential Service Investment ZHAO Wanmei, YE Chunming, DING Xiaodong 2023, 26 (5):  59-68.  doi: 10.3969/j.issn.1007-7375.2023.05.007 Abstract ( 768 )   HTML ( 690 )   PDF (1394KB) ( 869 )   Save This paper introduces two types of preferential service investment (reciprocal & self-interest) of downstream retailers in a dual-channel supply chain that adopts both traditional distribution and online direct sales modes. On the premise that product sales are sensitive to both prices and service, product sales are formulated based on customer utility to explore the impact of retailer preference service investment on decisions and profits of retailer themselves and upstream suppliers. Revenue sharing contracts through direct sales channels and dual channels are proposed aiming at the positive and negative spillover effects of supplier revenue, respectively, caused by the two types of preferential service investment of retailers, to achieve Pareto improvement of both sides’ revenue. Simulation examples are used to verify the theoretical analysis and experiment design. References | Related Articles | Metrics

Behavior-based Pricing on On-demand Platforms with Green Services under Competition CHEN Mingyang 2023, 26 (5):  69-77.  doi: 10.3969/j.issn.1007-7375.2023.05.008 Abstract ( 637 )   HTML ( 355 )   PDF (653KB) ( 832 )   Save To explore the phenomenon of behavior-based price (BBP) discrimination on on-demand platforms offering green services, a competition model consist of an on-demand platform offering green services and a traditional on-demand platform is established considering two scenarios (i.e., neither platform using BBP and both platforms using BBP). A two-period dynamic game-theoretic model is used to study how the adoption of BBP and implementation of green services affect various stakeholders. Results show that when green services are provided, there is a triple-win outcome; service providers can obtain higher (lower) payoffs when joining the platform in the first (second) period; when green services are provided, BBP generates lower profits given larger commission ratios, cost coefficient, and strength of consumer preference; however, the implementation of BBP results in lower profits when green services are not provided; moreover, BBP does not always lead to high consumer surplus, which depends on the trade-off between the two powers from market shares and service prices. References | Related Articles | Metrics

System Modeling & Optimization Algorithm

Multiple Dynamic Scheduling of Multi-objective Flexible Job Shops Based on a Hybrid Equilibrium Optimizer Algorithm QIN Hongbin, KONG Renjie, CHANG Yongshun, LI Chenxiao 2023, 26 (5):  78-88.  doi: 10.3969/j.issn.1007-7375.2023.05.009 Abstract ( 755 )   HTML ( 365 )   PDF (803KB) ( 932 )   Save To cope with the impact of multiple disturbances in production processes on actual scheduling processes, a multiple dynamic scheduling model for flexible job shops is established with urgent orders and machine breakdowns as disturbance factors and with the objectives of minimizing the makespan, order delay penalties and carbon emissions. A hybrid event- and cycle-based dynamic scheduling strategy is used to cope with emergencies, and an improved balanced optimizer algorithm is proposed to solve the model, which improves the initial population quality by adopting a hybrid population initialization strategy based on elite reverse learning. By using IPOX crossover, MPX crossover and mutation operations, the breadth and diversity of the algorithm is improved. An elite selection strategy based on Metropoils criteria is utilized to update the population and prevent it from falling into local optima. The searching ability of the algorithm is improved by double-layer variable neighborhood search. The effectiveness, stability and superiority of the algorithm are verified through a large number of extended numerical simulations. References | Related Articles | Metrics

Robust Optimization for Multi-skilled Project Scheduling with Uneven Resource Capacities HU Zhentao, CUI Nanfang 2023, 26 (5):  89-96,114.  doi: 10.3969/j.issn.1007-7375.2023.05.010 Abstract ( 730 )   HTML ( 351 )   PDF (932KB) ( 921 )   Save There are many uncertain factors during the implementation of real-life projects. Robust scheduling is an effective method to deal with uncertainties and reduce schedule deviations of a project. In addition, the multi-skilled resources with uneven capacities widely exist in real projects, which may increase the difficulty of scheduling. However, such resources can also enlarge the optimization space for robust project scheduling due to the flexible substitution and cooperation relationships among them. Based on this, a two-stage algorithm is proposed to solve the multi-skilled project scheduling problem with uneven resource capacities (URC-MSPSP). In the first stage, a rule-based heuristic algorithm is designed through combining activity priority rules and resource weight rules. A 0-1 linear programming model is built for solving the baseline scheduling plan and resource allocation strategies. Then in the second stage, a robust optimization algorithm is designed for the baseline scheduling plan by biased random insertion and deletion of time buffering, as well as the adjustment of resource allocation strategies.. Simulation experiments show that the proposed algorithm is significantly superior to other algorithms in terms of robustness for projects with different scales under different risk levels. References | Related Articles | Metrics

Joint Optimization for Layout and Allocation of Pick-up/Drop-off Points Using ACNS-MADS XIE Jieming, CHEN Qingxin, MAO Ning, ZHANG Huiyu 2023, 26 (5):  97-106.  doi: 10.3969/j.issn.1007-7375.2023.05.011 Abstract ( 675 )   HTML ( 350 )   PDF (1399KB) ( 896 )   Save Aiming at the joint optimization problem of location layout and capacity allocation of pick-up/drop-off points (P/D point) in cellar flow shops, an optimization model with throughput rates and cycle time constraints is established with the objective of minimizing the total transportation cost (including congestion cost) and allocation cost. According to the capacity balance between P/D points of adjacent processes and the problem characteristics of joint optimization of P/D point locations and capacities, a mesh adaptive direct search algorithm embedded with adaptive cooperative neighborhood search algorithm (ACNS-MADS) is proposed, in which the ACNS is used to reoptimize the P/D point location layout and capacity allocation scheme of a new solution. Experimental results show that compared with other algorithms, the total transportation cost and the P/D point allocation cost obtained by ACNS-MADS are reduced by 2.99% and 5.64% respectively, with a computation time reduction of over 17.95%. It can conclude that the proposed algorithm is effective and efficient to solve the joint optimization problem of P/D point layout and allocation, having practical value. References | Related Articles | Metrics

Inventory Optimization of Repairable Spare Parts for Civil Aircrafts with Incomplete Transshipment FU Weifang, FAN Xiangli, LIU Yingjie 2023, 26 (5):  107-114.  doi: 10.3969/j.issn.1007-7375.2023.05.012 Abstract ( 663 )   HTML ( 815 )   PDF (555KB) ( 941 )   Save The models and methods of spare parts inventory strategies that allow for complete sharing or unidirectional transshipment may not necessarily be applicable to all spare parts support systems. The inventory optimization problem of single echelon support systems is studied to further optimize the spare parts inventory strategy and operating cost of airlines, allowing mutual transshipment among multiple bases with incomplete sharing of repairable spare parts. The inventory of the system and bases is analyzed respectively according to Poisson distribution and Markov process theory. On this basis, an optimization model is established for the inventory of spare parts considering incomplete transshipment with the comprehensive support rate and the support rate of each base as constraints, and the objective being the minimum of total system cost. Then, the iterative algorithm and particle swarm optimization algorithm are constructed for solving the optimization problem. The results of AnyLogic simulation and sensitivity analysis of key parameters show that: the maximum relative error of each base support rate is 0.06, and the maximum relative error of the total system cost is 0.31% by comparing the optimization method and simulation calculation under the optimal configuration strategy in different situations. These results meet or very close to the target support rate requirements. Sensitivity analysis and error analysis show that the proposed model and algorithm are feasible and effective. References | Related Articles | Metrics

A Recommendation Method for Cloud Manufacturing Services Based on Graph Neural Networks DONG Xuewen, SHI Yuqiang, TIAN Yongzheng 2023, 26 (5):  115-123,167.  doi: 10.3969/j.issn.1007-7375.2023.05.013 Abstract ( 728 )   HTML ( 698 )   PDF (1155KB) ( 920 )   Save To address the problem of information overload caused by the massive manufacturing service information on cloud manufacturing service platforms, a graph neural network-based recommendation method for cloud manufacturing services is proposed in this paper, which effectively overcomes the limitations of traditional recommendation methods that cannot use high-dimensional features of data. Firstly, the features of manufacturing service resources on a platform are extracted, and manufacturing service resources are constructed as a network graph according to different similarity calculation methods. Secondly, a graph sample and aggregate (GraphSAGE) neural network is used for network representation learning, and the learned network features are brought into the link prediction function for model training. Finally, by predicting the link probability among resource nodes, the manufacturing service recommendation for users is completed. Experimental results show that the performance of the link prediction model based on GraphSAGE is better than that of link prediction models based on common neighbors (CN), Adamic-adar (AA) and resource allocation (RA). Thus, better recommendation results are achieved. It provides a theoretical basis for solving the recommendation problem of cloud manufacturing services and helps to improve the decision-making efficiency of users. References | Related Articles | Metrics

A Distributed Approximate Physical Integrated Commissioning Method for Production Lines Based on Digital Twins DENG Wenshun, LIU Qiang, ZHAO Rongli 2023, 26 (5):  124-130.  doi: 10.3969/j.issn.1007-7375.2023.05.014 Abstract ( 1311 )   HTML ( 366 )   PDF (1029KB) ( 908 )   Save In order to solve the problem of long cycle and high cost of production line designing and commissioning, the commissioning method and its application in manufacturing systems are studied. According to the characteristics of each method, a digital twins-based distributed approximate physical integrated commissioning method for production lines is proposed by integrating hardware-in-loop, software-in-loop and equipment-in-loop technology. Through establishing digital twins model for physical entities during the design phase, this method can conduct commissioning of production lines with virtual commissioning for the design scheme, semi-physical commissioning for the controller and equipment-in-loop commissioning for the synchronization of virtuality and reality. Also, it supports sectional no-load integrated commissioning for multiple suppliers' equipment to improve the commissioning and validation processes of remote equipment and production line control logic during the integration process of intelligent workshop production lines. Finally, the effectiveness of the method is verified based on a digital twins system (DTS) through a case of a motor assembly line. References | Related Articles | Metrics

Collaborative Optimization of Multi-skilled Workers and Task Assignment Considering Lot-splitting in Seru Production WU Yinghui, ZENG Shaoyu, CHEN Sisi 2023, 26 (5):  131-138.  doi: 10.3969/j.issn.1007-7375.2023.05.015 Abstract ( 655 )   HTML ( 696 )   PDF (839KB) ( 876 )   Save Existing studies on workers and task assignment in a Seru system usually focus on improving production efficiency, which may cause workload imbalance among workers. To cope with this issue, with the aim of mitigating workload imbalance among workers, this paper jointly optimizes multi-skilled workers and task assignment in a Seru production system with the consideration of lot-splitting. A mixed-integer nonlinear programming model is proposed to minimize the maximum workload of workers. To verify the effectiveness of the proposed model, comparison models without lot-splitting and with lot-splitting but optimizing production efficiency are built. By introducing continuous variables and inequalities, these models are linearized and solved by optimization solver CPLEX based on different-scales instances. Numerical experiments show that compared with the model without lot-splitting, our model has better performance in improving the fair distribution of workers’ workload, with an average reduction of 5.40% in maximum workload of each worker, while maintaining a high level of production efficiency. The studied results can not only supplement the existing optimization theory of a Seru production system, but also provide more valuable guidance for actual production decision-making of enterprises from the perspective of workload equity. References | Related Articles | Metrics

A Passenger Flow Simulation and Organization Optimization of Hub Stations Based on Self-learning Agent Model FU Hui, YAO Yipeng, CHEN Saifei 2023, 26 (5):  139-148.  doi: 10.3969/j.issn.1007-7375.2023.05.016 Abstract ( 1234 )   HTML ( 360 )   PDF (1959KB) ( 824 )   Save In order to guarantee free passenger flows in a hub station with a given flow line, the station can adjust the facility deployment, design building structures and passenger service processes, to reduce the conflicts, so as to improve the efficiency of passenger flows and make an optimization of passenger flow organization. This paper first establishes an agent-based simulation framework to describe detailed passenger behavior in a hub station from the optimization and organization of passenger flows. Then, a passenger flow simulation for hub stations is developed based on the proposed framework, and the reliability of the proposed simulation is verified by combining real data. Finally, the optimization strategy of passenger flow organization is generated by applying the proposed simulation. Results show that the proposed agent model and its method can support the simulation of passenger flow within a hub station and simulate the movement behaviour of passengers in facilities with relatively small errors. The facility optimization strategy can save the redundant facility capacity of the inbound flow line in Guangzhou South Railway Station. References | Related Articles | Metrics

Life Span Prediction of Key Fixtures Integrating Principal Component Analysis and Random Forest Model ZHU Xiaofeng, XU Manfei, LIU Zhihong, LENG Jiewu 2023, 26 (5):  149-158.  doi: 10.3969/j.issn.1007-7375.2023.05.017 Abstract ( 694 )   HTML ( 1031 )   PDF (1226KB) ( 942 )   Save To address the difficulties in predicting the remaining life span of key fixtures in assembly of initiating explosive product and providing reference for field data, a life span prediction model of key fixtures for initiating explosive product assembly is established integrating assembly feature extraction and minimization of impurity weighted sum. In addition, a prototype of a life span prediction system for key fixtures in initiating explosive product assembly is developed. In this paper, assembly features of key fixtures are extracted by principal component analysis, while the remaining life span of key fixtures is predicted by random forest model. Comparative analysis shows that, compared with traditional methods, the prediction accuracy of the proposed method is increased by 0.89%, and the mean square error, root mean square error and prediction time are decreased by 22.3%, 22.3% and 24.8%, respectively. It is proved that the method has the advantages of high prediction accuracy, good stability and fast prediction speed. References | Related Articles | Metrics

Traffic Flow Prediction for Large-scale Road Network Based on Graph Transformer DONG Chengxiang, WEI Xin, ZHANG Kunpeng, WANG Yongchao 2023, 26 (5):  159-167.  doi: 10.3969/j.issn.1007-7375.2023.05.018 Abstract ( 692 )   HTML ( 364 )   PDF (1244KB) ( 1117 )   Save To accurately predict traffic flow in large-scale road networks, a traffic flow prediction model is proposed based on Graph Transformer to capture the complex and dynamic spatiotemporal characteristics of traffic flows. Gate recurrent unit (GRU) module is adopted in the model to extract temporal features of historical traffic flow data in a road network. According to the connections among sensors distributed in a network, traffic graphs are then established with historical traffic flows as nodes and connections of sensors as edges. On this basis, spatiotemporal characteristics are captured using Graph Transformer-based deep learning technologies. To verify the effectiveness of the proposed model, comparisons with six baseline models using the PeMS highway dataset are conducted. Experiments show that the proposed prediction model results in the best performance. References | Related Articles | Metrics