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30 April 2023, Volume 26 Issue 2 Previous Issue    Next Issue

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System Analysis & Management Decision

Distribution Mode Selection of Fresh Food E-Commerce Enterprises under Competitive Environment NIE Jiajia, XU Xiaoxuan 2023, 26 (2):  1-11.  doi: 10.3969/j.issn.1007-7375.2023.02.001 Abstract ( 1523 )   HTML ( 128290 )   PDF (1111KB) ( 2822 )   Save The strategy selection of logistics distribution modes for fresh food e-commerce under competitive environment is studied in this paper. Nash static game method is used to solve the equilibrium retail price, demand and profit of the two fresh food e-commerce enterprises with two modes of self-operated logistics and third-party logistics (platform logistics) for selection under competitive environment. Results show that: when the commission ratio is low, both fresh food e-commerce enterprises choose the third-party logistics distribution mode; when the commission ratio is high, both fresh food e-commerce enterprises choose self-operated logistics distribution mode. Furthermore, the interests of the two fresh food e-commerce enterprises are not always opposite. When the commission ratio is low and the price competition intensity of fresh products is large or the commission ratio is moderate, the two e-commerce enterprises can achieve a win-win situation. The profits of the two e-commerce enterprises are also related to their market share. When the commission rate is higher, the profits of the two e-commerce enterprises are more affected by their market share. In addition, the decision-making process of two fresh e-commerce enterprises is also analyzed. The choice of distribution mode of fresh food e-commerce enterprises is not only related to the commission rate, but also closely related to the intensity of price competition between the fresh products they provide. References | Related Articles | Metrics

A Pricing Strategy of Green Supply Chain Based on Stochastic Reference Prices LIN Zhibing, WU Qing 2023, 26 (2):  12-19,30.  doi: 10.3969/j.issn.1007-7375.2023.02.002 Abstract ( 984 )   HTML ( 21423 )   PDF (1087KB) ( 1834 )   Save In order to study the effect of consumers' stochastic reference prices on the pricing decision of green supply chain, a green supply chain model with retailer's risk aversion is established. The optimal equilibrium is obtained and a sensitivity analysis is conducted through the Stackelberg game method and optimization theory. Then, a combined contract of sharing revenue and cost is designed to coordinate the green supply chain. In addition, the proposed model is extended to analyze the impact of information asymmetry on channel members. The study finds that: 1) the expected profits of manufacturers and channels increase with the increase in the deviation of stochastic reference prices, while those of retailers increase first and then decrease with the deviation of stochastic reference prices; retailer's risk aversion and the deviation of stochastic reference prices have similar effects on channel members' expected profits; 2) the more sensitive consumers are to stochastic reference prices, the more detrimental it is to both manufacturers and retailers; 3) information asymmetry is not beneficial to manufacturers, nor is it necessarily beneficial to retailers. References | Related Articles | Metrics

A Closed-loop Supply Chain Financing Model Considering Risk Preference of Growing Enterprises MI Liyang, SHANG Chunyan, QIU Ruozhen 2023, 26 (2):  20-30.  doi: 10.3969/j.issn.1007-7375.2023.02.003 Abstract ( 1018 )   HTML ( 21359 )   PDF (1319KB) ( 1791 )   Save In a closed-loop supply chain system composed of a single manufacturer and a single growing retailer, aiming at the randomness of market demand and capital constraints of the growing retailer, and considering the bilateral risk preferences of the supply chain, four closed-loop supply chain operation modes are established based on the mean-standard deviation criterion. The effects of risk preference, financing interest rates and self-owned funds on the closed-loop supply chain operation modes are analyzed. Results show that the profits of both sides in the supply chain are positively correlated with their own risk preferences and negatively correlated with each other’s risk preferences, thus, the manufacturer is more willing to cooperate with the retailer with risk aversion, and vice versa; when self-owned funds are low, it is more advantageous for the retailer to choose non-compensatory deferred payment mode, while when self-owned funds are high, the retailer tends to choose bank lending mode; when the transfer payment quota meets certain conditions, the market development contract can achieve Pareto improvement in the supply chain, so as to help the growing retailer capture growth opportunities and achieve rapid development. References | Related Articles | Metrics

An Order Batching Problem Based on Joint Picking and Sorting FENG Ailan, ZHOU Manman, YANG Lechang 2023, 26 (2):  31-39,66.  doi: 10.3969/j.issn.1007-7375.2023.02.004 Abstract ( 900 )   HTML ( 21079 )   PDF (1137KB) ( 1772 )   Save This paper studies the order batching problem in an accumulation/sortation system which combines partitioned sorting and automatic circular sorting lines. A multi-objective order batching and scheduling model is proposed to minimize the number of delayed orders and the average delay time. Variable neighborhood search (VNS) algorithm is applied to solve the problem, and the passive wave division is adopted to alleviate the congestion in sorting lines. Results of the case analysis show that: when the order arrival rate λ=5, compared to the order batching strategy considering picking only, the batch strategy of joint picking and sorting gives the optimization rates of the number of delayed orders and the average delay time as 88.8% and 80.4%, respectively, under the FCFS assignment rule, while the optimization rates of both indicators as 100% under the fixed priority rule. It proves that the batch strategy of joint picking and sorting has a good effect in reducing the number of delayed orders. Finally, by discussing the order arrival rate and the number of delivery channels, a sensitivity analysis is conducted to further promote the experimental results and provide the basis for parameter selection. References | Related Articles | Metrics

An Investing Preventive Maintenance Strategy to Reduce the Whole Machine and Component Failures MO Simin, LI Xi 2023, 26 (2):  40-49.  doi: 10.3969/j.issn.1007-7375.2023.02.005 Abstract ( 813 )   HTML ( 20402 )   PDF (934KB) ( 1759 )   Save To prevent the failure of large equipment products caused by key components provided by suppliers, a warranty strategy to invest in the preventive maintenance costs for such key components is proposed. By establishing a cost model of investing in preventive maintenance, the win-win interval of preventive maintenance investment for the customer and the manufacturer, as well as for the manufacturer and the supplier, is obtained. The effects of failure rate and various costs on the win-win interval and tri-win interval are investigated through theoretical and numerical analysis, leading to the optimal preventive maintenance strategy, optimal win-win interval and optimal tri-win interval. The results show that the warranty strategy of investing in the cost of preventive maintenance during the warranty period is applicable to large equipment products, where the higher the failure rate of key components provided by the supplier and the longer the repair time after failure, the lower the cost of implementing preventive maintenance. References | Related Articles | Metrics

Fault Prediction of Decentralized Stochastic Discrete-Event Systems Based on Dynamic Observations LIAO Hui, LIU Fuchun 2023, 26 (2):  50-58.  doi: 10.3969/j.issn.1007-7375.2023.02.006 Abstract ( 769 )   HTML ( 19612 )   PDF (2140KB) ( 1735 )   Save In order to solve the problem that the current event observability of stochastic discrete-event systems (SDESs) is fixed in advance and cannot be changed dynamically with system evolution, a decentralized fault prediction method based on dynamic observations is proposed. First, the D-copredictability of decentralized SDESs under dynamic observations is formalized. Then, in order to conduct the fault prediction of decentralized SDESs with dynamic observations, a D-copredictor is established using local stochastic predictors. A necessary and sufficient condition of D-copredictability for decentralized SDESs based on the D-copredictor is presented, while an algorithm for verifying the D-copredictability of SDESs is proposed. The proposed verification algorithm can be used not only for online fault prediction, but also for offline predictability verification. Finally, the applicability of the verification algorithm for decentralized fault prediction under dynamic observation is analyzed. References | Related Articles | Metrics

Duration Prediction of Power Business Expansion Project Based on ICSO-SOM-ELM LIN Jingxing, ZHOU Xin, XIE Zhiwei, XU Xuancong, ZHANG Zheng 2023, 26 (2):  59-66.  doi: 10.3969/j.issn.1007-7375.2023.02.007 Abstract ( 790 )   HTML ( 18806 )   PDF (1172KB) ( 1720 )   Save Aiming at the uncertainty of power business expansion project duration, an ICSO-SOM-ELM prediction model of power business expansion project duration is proposed based on self-organizing map network clustering and improved crisscross algorithm to optimize the weight threshold of extreme learning machine. Firstly, based on the project budget cost and the number of nodes, the self-organizing map network is used to secondarily cluster the data of power business expansion project, so as to preliminarily reduce the confusion of the original data set. Secondly, an improved crisscross algorithm based on the mechanism of neighborhood population crossover and mutation is proposed, which is used to optimize the weight threshold of an extreme learning machine model to obtain the optimal ELM prediction model. Finally, according to the secondary clustering data of power business expansion projects, an ICSO-ELM prediction model is used to predict the project duration. An experiment is conducted with the business expansion data of a power supply company. Results show that the proposed ICSO-SOM-ELM prediction model is better than other ones, verifying its effectiveness and providing scientific suggestions for duration planning of power supply companies’ business expansion projects. References | Related Articles | Metrics

Product Pricing Strategies Considering Consumers' Online and Offline Switching Purchase Behavior LI Hao, XIAO Qing 2023, 26 (2):  67-76,110.  doi: 10.3969/j.issn.1007-7375.2023.02.008 Abstract ( 828 )   HTML ( 18838 )   PDF (1110KB) ( 1919 )   Save In view of the sales dilemma of retailers brought by consumers’ online and offline switching purchase behavior, based on the dynamic pricing model, a two-period two-retailer price matching game model is constructed. The simplified calculation method of the proposed model is discussed, while the effectiveness of the price matching strategy and the optimal pricing strategy of products are further analyzed, so as to provide theoretical support for retailers’ product pricing. Results show that: the number of consumers arriving at the beginning of the time period and the perception difference between online and offline products are important factors affecting their decisions, which have a great impact on the expected returns of the two retailers; the proposed price matching strategy can induce consumers to have different switching purchase behaviors by adjusting the product pricing, and then optimize the retailers' revenue; the online retailer always tends to actively match the prices of the offline products, and alleviate price competition between two retailers when the perception difference between online and offline products are large, achieving Pareto improvement in the market; the offline retailer can also actively implement price matching strategies, but the effect of revenue improvement is more obvious when the perception difference between products is small. References | Related Articles | Metrics

Decisions on Purchase of Enterprise Emission Rights under the Scenario of Uncertain Emission Right Prices NIU Yifei, JIN Shuai 2023, 26 (2):  77-84,122.  doi: 10.3969/j.issn.1007-7375.2023.02.009 Abstract ( 792 )   HTML ( 19161 )   PDF (1070KB) ( 1730 )   Save In order to optimize the number of emission rights purchased by an enterprise with limited rationality under the system with paid use and trading of emission rights, we study the influence of risk preference on enterprise decision-making in the context of uncertain emission right trading prices. The relationship between the purchase decision and other production decisions of an enterprise is analyzed, accordingly a purchase planning model is then given. The return risk is measured using variance and semi-variance, while the purchase decisions of enterprises with different risk preferences are further optimized by mean-variance and semi-variance models. Results show that the purchase decision of an enterprise’s emission rights is separated from other production decisions; the optimal purchase decision of an enterprise’s emission rights is affected by the market price of emission right trading, but not by the fluctuation range of market prices; and the purchase decisions of enterprises with different risk preferences are positively correlated with their risk tolerance and lower limit of expected return. In addition, compared to the optimization model that use variance to measure risk, the maximum profit and minimum risk of the optimization results by using semi-variance are both better than those obtained by the former, leading to that semi-variance is more suitable as an indicator of an enterprise to analyze the return risk in practice. References | Related Articles | Metrics

System Modeling & Optimization Algorithm

A Construction Scheduling Optimization of Prefabricated Buildings Based on Improved NSGA-II Algorithm WANG Heping, GONG Xinglin, LI Yan 2023, 26 (2):  85-92.  doi: 10.3969/j.issn.1007-7375.2023.02.010 Abstract ( 949 )   HTML ( 18278 )   PDF (964KB) ( 1997 )   Save In view of the previous studies on prefabricated building scheduling with only a certain activity time and one execution mode for each activity, while actual scheduling processes are with uncertain activity time and various execution modes of activities, a fuzzy scheduling model with multi-objective and multi-mode resource constraints is established. An improved non-dominated sorting genetic algorithm (INSGA-II) is proposed to solve the (time-cost) bi-objective optimization model. The proposed algorithm performs population initialization and crossover operations according to the priority relationship of activities, meanwhile, a new three-segment coding method is developed containing activity, mode and resource lists. Finally, through the case analysis of an actual prefabricated building construction site and the comparison of algorithm performance, it is proved that the proposed scheduling model and algorithm can effectively solve the fuzzy scheduling problem under multi-mode resource constraints. It provides scientific ideas and methods for the design of construction scheduling plan. References | Related Articles | Metrics

Modeling and Optimization on Two-echelon Inventory Allocation of Repairable Spar Parts Considering False Alarms from a Performance Assurance Perspective ZHANG Zhiying, ZHANG Jiale, ZHANG Bang, LIU Rumeng 2023, 26 (2):  93-100.  doi: 10.3969/j.issn.1007-7375.2023.02.011 Abstract ( 844 )   HTML ( 16536 )   PDF (730KB) ( 1710 )   Save In the case of false alarms, the inventory allocation of repairable spare parts is overestimated, and the inventory allocation of each station deviates from the demand. Combining the Metric theory, the characteristics of the two-echelon repairable spare parts support process are analyzed. The false alarm fault identification coefficient in the maintenance process is introduced to modify the average demand for spare parts of at each support station. Considering the cost of fault maintenance and false alarm identification, and satisfying the requirements of system performance indicators, an inventory allocation model aiming to minimizing the support cost is established. The marginal optimization algorithm is used for numerical analysis. By comparing the spare parts inventory allocation strategies with and without false alarms, it is proved that the model considering false alarms can improve the estimation accuracy of the two-echelon repairable spare parts inventory allocation. References | Related Articles | Metrics

An Improved Moth-flame Optimization Algorithm for Solving High-dimensional Complex Functions LI Yu, ZHU Xinya, LIU Jingsen 2023, 26 (2):  101-110.  doi: 10.3969/j.issn.1007-7375.2023.02.012 Abstract ( 788 )   HTML ( 15108 )   PDF (1015KB) ( 1691 )   Save A moth-flame optimization algorithm with adaptive dynamic disturbance coefficient and piecewise adjustable search strategy (ADMFO) is proposed to solve a large-scale complex optimization problem. The adaptive dynamic perturbation coefficient strategy is adopted to improve the global searching ability of the algorithm and avoid the algorithm falling into the local optimum. The segmented search strategy can balance the proportion of global exploration and local development, so as to achieve a better search strategy. 15 unimodal and multi-peak complex high-dimensional function optimization experiments are conducted, comparing particle swarm algorithm, sine cosine algorithm, butterfly optimization algorithm, the gray wolf algorithm, and the four improved algorithms proposed in other literature. The experimental data proves that the improved algorithm has better optimization accuracy and stability. References | Related Articles | Metrics

An Optimal Configuration of Agri-food Supply Chain Based on Labor Resource Constraints and Uncertain Demand NIE Duxian, TANG Jiayan, ZHAO Jinying, QU Ting 2023, 26 (2):  111-122.  doi: 10.3969/j.issn.1007-7375.2023.02.013 Abstract ( 834 )   HTML ( 14196 )   PDF (1117KB) ( 1812 )   Save In order to explore the impacts of the COVID-19 pandemic on agri-food supply chain, a study is conducted on the optimal configuration of multi-stage agri-food supply chain under labor resource constraints and uncertain market demand. A nonlinear programming model is established. Taking a large enterprise of wheat and wheat flour derivatives supply chain as an example, the adaptive ant colony algorithm (ACA) is adopted to solve the model. The solutions obtained by the optimization tool Lingo are compared to verify the effectiveness of ACA. Finally, sensitivity analysis is conducted on different external market demand and labor resource constraints, and some important management implications are obtained. References | Related Articles | Metrics

An Adaptive Large Neighborhood Search Algorithm for Pickup and Delivery Problem with Time Windows and Weight-related Cost WU Tingying, WANG Chenxiu, SUN Hao 2023, 26 (2):  123-131.  doi: 10.3969/j.issn.1007-7375.2023.02.014 Abstract ( 903 )   HTML ( 14428 )   PDF (523KB) ( 1959 )   Save The rapid growth of logistics distribution demand makes an increasing wide application of pickup and delivery. A pickup and delivery problem with time windows and weight-related cost is studied, considering that the cargo weight has an effect on the transportation cost in the distribution process. A bi-objective mixed integer programming model of the problem is formulated to minimize the number of vehicles and the total transportation cost, in which the transportation cost is a function of vehicles’ load capacities and travel distances. A two-stage adaptive large neighborhood search algorithm is designed to solve the model, where the performance is improved by designing multiple efficient destroy and repair operators and introducing a simulated annealing strategy to avoid local optimal. Instances with different scales and characteristics are tested, showing that the proposed two-stage adaptive large neighborhood search algorithm can solve small-scale, middle-scale and large-scale instances effectively. Also, the impact of cargo weight and different transport coefficients on transportation cost is analyzed, providing reference for logistics enterprises to optimize the route of pickup and delivery vehicles. References | Related Articles | Metrics

Vehicle Routing Optimization and Its Algorithm Considering Driver Fatigue ZHANG Shuzhu, QIU Bingbing, SHAN Jiajun, LONG Qingqi 2023, 26 (2):  132-140,184.  doi: 10.3969/j.issn.1007-7375.2023.02.015 Abstract ( 1650 )   HTML ( 13802 )   PDF (1118KB) ( 1790 )   Save In urban logistics, drivers are facing a high-intensity work environment. In view of this, the dynamic changes of drivers’ ability to deliver caused by fatigue is considered in delivery processes, and a vehicle routing optimization model is established with the minimization of total delivery time as the objective. A delivery speed function based on fatigue degree is introduced into the model to quantify the change of drivers' ability to deliver. Then, a modified artificial bee colony algorithm is designed to solve the model integrated with the breadth-first and depth-first search strategies. Finally, the effectiveness of the proposed model and algorithm is verified through standard testing sets and simulation experiments. Experimental results show that considering the impact of driver fatigue is helpful to maintain the balance of drivers' workload and reduce the degree of driver fatigue. The results of this study may have an important reference significance for delivery planning of logistics enterprises. References | Related Articles | Metrics

Route Decisions on Container Multimodal Transportation Considering Transportation Network Risk PEI Yingmei, LIU Lihui 2023, 26 (2):  141-147.  doi: 10.3969/j.issn.1007-7375.2023.02.016 Abstract ( 935 )   HTML ( 13646 )   PDF (706KB) ( 1804 )   Save Considering the risk of transportation network, the route decision of container multimodal transportation is studied. By using risk factors and the dynamic programming method to analyze the reliability of a transportation network, a route decision objective programming model for container multimodal transportation is established by comprehensively considering the transportation network risk, transportation time, transportation cost and cargo damage. To solve this model, a hybrid algorithm of genetic and ant colony algorithms is designed. Multiple initial routes including set nodes and edges are found through a route selection model. Then, dynamic programming combined with risk factors is used to obtain the alternative solutions at key nodes and edges of each route. Finally, the optimal route is found by using a multi-objective multimodal transportation model to maximize the resistance to transportation network risk. A container export case from Xiamen to Almaty is taken as an example to prove the effectiveness of the proposed model and algorithm, which can provide a reference for route decisions by comprehensively taking the economy, timeliness and safety of container multimodal transportation into consideration. References | Related Articles | Metrics

Marshalling Plan Optimization for Single-group Freight Trains in the Direction of Straight-line Railways Considering the Balance of Operating Capacity HUANG Wei, HU Peiqi, LIU Yinke 2023, 26 (2):  148-154.  doi: 10.3969/j.issn.1007-7375.2023.02.017 Abstract ( 808 )   HTML ( 12453 )   PDF (430KB) ( 1750 )   Save Railway freight transportation plays a pivotal role in ensuring the continued stability of the national economy and fighting the impact of the epidemic. For goods with different transportation destinations and origins, it is necessary to effectively organize the origins of goods and improve the transportation efficiency by using the operating capacity of each marshalling station while ensuring low time consumption for the running of marshalling trains. Focusing on the marshalling optimization of single-group freight trains among stations in a straight-line direction, this paper aims to minimize the sum of the hourly consumption of assembled trains at stations and the hourly consumption of remarshalling transit trains along the way. Considering the limitations of the uniqueness of remarshalling strategies for traffic flows, the remarshalling capacity of stations, and the capacity of a shunting line, a multi-objective linear 0-1 programming model is established based on the linear integer programming model of the traditional single train marshalling plan at stations, adding the constraint of no remarshalling passing through the stations along the way. A small-scale example is adopted for solving and analysis to verify the accuracy and practicability of the model, and further improve the efficiency of railway freight transportation. References | Related Articles | Metrics

A Dynamic Optimization Method of Material Distribution Intervals and Quantity for Bearing Flexible Intelligent Manufacturing LI Hongyan, YANG Xiaoying, ZHAO Hengzhe, ZHANG Zhiwen 2023, 26 (2):  155-162.  doi: 10.3969/j.issn.1007-7375.2023.02.018 Abstract ( 868 )   HTML ( 11339 )   PDF (917KB) ( 1746 )   Save Aiming at the problem that traditional material distribution methods are difficult to meet the requirements of flexible intelligent manufacturing of bearings, an adaptive optimization method of material distribution intervals and quantity with multiple varieties and variable batch size is proposed. First, taking the distribution cost, the cost of inventory beside a production line and the number of automated guided vehicles as the optimization objectives, and taking the material quantity, the distribution capacity of automated guided vehicles and the distribution time as constraints, a multi-objective cooperative optimization model for distribution intervals and quantity of multi-frequency and small-batch materials is established. Then, according to the characteristics of the decision variables in the optimization model, using real values that reflect distribution information for coding, a fast non-dominated sorting genetic algorithm is designed with modified crowding calculation method and elitism strategy to improve the optimization ability of genetic algorithm. Finally, the proposed optimization method is verified with an application example. Results show that: compared to non-optimized scenarios, the average distribution batch size is reduced by 42%, the average distribution interval is shortened by 30%, and the total distribution cost can be reduced by more than 17% after optimization, which realizes the self-adaptation and self-decision of material distribution intervals and quantity under different bearing types, and effectively reduces the total distribution cost. References | Related Articles | Metrics

Design of Recycling Networks for Demolition and Construction Wastes under Carbon Policies and Landfill Constraints JI Xiang, WANG Jiuhe, SUI Yiting 2023, 26 (2):  163-175.  doi: 10.3969/j.issn.1007-7375.2023.02.019 Abstract ( 822 )   HTML ( 9536 )   PDF (1002KB) ( 1652 )   Save Focusing on the fuzziness and randomness in the recycling logistics of demolition and construction wastes, the design of recycling networks under different carbon emission policies is studied. A fuzzy-stochastic programming model with objectives being maximizing system profit and minimizing waste landfills is established; the fuzzy objectives and constraints are transformed through expected intervals and expected values of fuzzy numbers; the sample average approximation method and the ε-constraint method are used to cope with random parameters and transform the landfill objective into constraints; taking the renovation project of shanty towns in Qingdao as a case study, a numerical analysis is conducted, where the model is solved by gurobi. Results show that: the system is more profitable under a carbon trading policy when the proportion of landfills allowed is high (rL>34%) and more profitable under a carbon tax policy when the proportion of landfills allowed is low (rL<34%); when there is a strict landfill constraint (rL=30%), carbon emission policies basically do no work in carbon reduction; with a mixed policy and no landfill constraint, the government's regulation of carbon trading price level and fluctuation can balance the carbon emission and waste landfills of recycling networks. References | Related Articles | Metrics

Optimization of Human Resources at International Settlement Counters in Airports ZHOU Junyi, MAO Ning, CHEN Qingxin, HU Changwei, CHENG Yu, YU Longshui 2023, 26 (2):  176-184.  doi: 10.3969/j.issn.1007-7375.2023.02.020 Abstract ( 795 )   HTML ( 1107304560 )   PDF (1182KB) ( 1605 )   Save The number of customers served by the international settlement counter in an airport fluctuates greatly with flight conditions, which is a non-steady and random process. Utilizing queuing theory to perform a smooth approximation time by time and calculate the number of service staff required in each period, may give an inaccurate result. To solve this problem, we first analyze the average service speed of a counter staff, while the arrival of customers that need to be served on each flight is predicted based on flight information. Then, GI/G/m queuing theory model is adopted to calculate the number of service staff required in each time period as an approximate initial solution for human resource allocation. Furthermore, a simulation model is built to optimize the number of service staff required in each time period at a counter. Finally, the simulation optimization results are compared with the approximate solutions, and the reasons for their differences are analyzed, providing a decision-making basis for the staffing and scheduling of an international settlement counter. References | Related Articles | Metrics