考虑混合工艺的自动化码头多设备资源协同调度优化模型和算法设计

Considering the uncertainty of the speed of horizontal transportation equipment,a cooperative scheduling model of multiple equipment resources in the automated container terminal was constructed to minimize the completion time,thus improving the loading and unloading efficiencies of automated container terminals.The proposed model integrated the two loading and unloading processes of“double-trolley quay crane+AGV+ARMG”and“single-trolley quay crane+container truck+ARMG”and then designed the simulated annealing particle swarm algorithm to solve the model.By comparing the results of the particle swarm algorithm and genetic algorithm,the algorithm designed in this paper could effectively improve the global and local space search capability of finding the optimal solution.Furthermore,the results showed that the proposed method of collaborative scheduling of multiple equipment resources in automated terminals considering hybrid processes effectively improved the loading and unloading efficiencies of automated container terminals.The findings of this study provide a reference for the improvement of loading and unloading processes as well as coordinated scheduling in automated terminals.

Dynamic Pricing Research for Container Terminal Handling Charges based on Demand Forecast

A dynamic pricing model was established based on forecasting the demand for container handling of a specific shipping company to maximize terminal profits to solve terminal handling charges under the changing market environment.It assumes that container handling demand depends on the price and the unknown parameters in the demand model.The maximum quasi-likelihood estimation(MQLE)method is used to estimate the unknown parameters.Then an adaptive dynamic pricing policy algorithm is proposed.At the beginning of each period,through dynamic pricing,determining the optimal price relative to the estimation value of the current parameter and attach a constraint of differential price decision.Meanwhile,the accuracy of demand estimation and the optimality of price decisions are balanced.Finally,a case study is given based on the real data of Shanghai port.The results show that this pricing policy can make the handling price converge to the stable price and significantly increase this shipping company’s handling profit compared with the original“contractual pricing”mechanism.

Effects of methionine treatment on storage quality and antioxidant activity of postharvest jujube fruit

Jujube fruits usually suffer from physiological disorders or infectious diseases during storage,leading to quality deterioration,softening,or rotting.Therefore,this study aims to investigate the effect of methionine soaking treatment on the postharvest jujube fruit decay rate and storage quality.Methionine treatment significantly reduced the decay rate of postharvest jujube fruit and effectively maintained fruit color and titratable acid.Methionine treatment effectively delayed the decrease of firmness,soluble solids,ascorbic acid,and lignin contents in jujube fruit.Methionine treatment reduced the content of alanine and phenylalanine,and increased the content of glycine in jujube fruit,but displayed no significant effect on total amino acid content.In addition,jujube fruits in the methionine treatment group had a higher total phenolic and flavonoid content and antioxidant capacity,both in free and bound forms.Compared with the control,methionine treatment also significantly increased the content of individual phenolic acid fractions(gallic acid,vanillic acid,and syringic acid)and flavonoid fractions(catechin,epicatechin,rutin)in free form as well as individual phenolic acid fractions in bound form(gallic acid and ferulic acid)in jujube fruits.Overall,this study suggested that the methionine treatment could be used as a prospective preservative to reduce the postharvest decay of jujube fruit and alleviate its nutritional quality deterioration during cold storage at 4°C.

Understanding changes in volatile compounds and fatty acids of Jincheng orange peel oil at different growth stages using GC-MS

Jincheng orange(Citrus sinensis Osbeck)is widely grown in Chongqing,China,and is commonly consumed because of its characteristic aroma contributed by the presence of diverse volatile compounds.The changes in aroma during the development and maturation of fruit are indicators for ripening and harvest time.However,the influence of growth stages on the volatile compounds in Jincheng orange remains unclear.In addition,volatiles originate from fatty acids,most of which are the precursors of volatile substances.On this basis,gas chromatography-mass spectrometry(GC-MS)was performed to elaborate the changes in volatile constituents and fatty acids as precursors.This study tested proximately 60 volatiles and 8 fatty acids at 9 growth and development stages(AF1-AF9).Of those compounds,more than 92.00%of total volatiles and 87.50%of fatty acids were terpenoid and saturated fatty acids,respectively.As shown in the PCA plot,the AF5,AF6,and AF9 stages were confirmed as completely segregated and appeared different.In addition,most of the volatiles and fatty acids first increased at the beginning of the development stage,then decreased from the AF6 development stage,and finally increased at the AF9 maturity stage.Moreover,the highest contents of terpenoid,alcohols,aldehydes,ketones,and saturated fatty acids in Jincheng orange peel oil were d-limonene,linalool,octanal,cyclohexanone,and stearic acid during development stages,respectively.Our results found that the growth stages significantly affected the volatile constituents and precursors in Jincheng orange peel oil.

An improved cellular automaton model considering the effect of traffic lights and driving behaviour

This paper proposes an improved cellular automaton model to describe the urban traffic flow with the consideration of traffic light and driving behaviour effects. Based on the model,the characteristics of the urban traffic flow on a single-lane road are investigated under three different control strategies,i.e.,the synchronized,the green wave and the random strategies. The fundamental diagrams and time-space patterns of the traffic flows are provided for these strategies respectively. It finds that the dynamical transition to the congested flow appears when the vehicle density is higher than a critical level. The saturated flow is less dependent on the cycle time and the strategies of the traffic light control,while the critical vehicle density varies with the cycle time and the strategies. Simulated results indicate that the green wave strategy is proven to be the most effective one among the above three control strategies.

Effects of INA on postharvest blue and green molds and anthracnose decay in citrus fruit

As a synthetic functional analog of salicylic acid, 2,6-dichloroisonicotinic acid(INA) is effective in inducing the host disease resistance of a plant against a pathogen. The effects of INA on controlling postharvest blue and green molds and anthracnose decay and defense-related enzymes on citrus fruits were investigated, and the ascorbic acid of naturally infected citrus flavedo was also measured. Results showed that 1.0 mmol L^(–1) INA treatments significantly reduced blue and green molds and anthracnose decay development on both wound-inoculated fruit and naturally-infected fruit compared with the control fruit. The treatment effectively enhanced the β-1,3-glucanase(GLU), chitinase(CHI), phenylalanine ammonia-lyase(PAL) and peroxidase(POD) activities and the polyphenol oxidase(PPO) in flavedo. The results presented here suggest that INA might be used as a chemical fungicide substitution to control postharvest diseases in citrus fruits.

The RHSA Strategy for the Allocation of Outbound Containers Based on the Hybrid Genetic Algorithm

安全存储院子是容器交通的最佳的核心目标之一；因此，做必要存储安排成为了容器终端管理系统(CTMS ) 的最关键的部分。这篇论文为随机进入院子的开往外地的集装箱调查一个随机的混合的叠算法(RHSA ) 。在 RHSA 的第一个阶段，在块之中的分发关于利用比率被分析。在第二个阶段，海湾配置的优化被使用混合基因算法执行。而且，一个实验被执行测试 RHSA。结果证明探索算法是有用的增加效率。

Evacuation of pedestrians from a hall by game strategy update

In this paper, a cellular automaton model considering game strategy update is proposed to study the pedestrian evacuation in a hall. Pedestrians are classified into two categories, i.e., cooperators and defectors, and they walk to an exit according to their own strategy change. The conflicts that two or three pedestrians try to occupy the same site at the same time are investigated in the Game theory model. Based on it, the relationship between the pedestrian flow rate and the evacuation time as well as the variation of cooperative proportion against evacuation time is investigated from the different initial cooperative proportions under the influence of noise. The critical value of the noise is found when there is a small number of defectors in the initial time. Moreover, the influences of the initial cooperative proportion and strength of noise on evacuation are discussed. The results show that the lower the initial cooperative proportion as well as the bigger the strength of noise, the longer the time it takes for evacuation.

Suggestion of Maintenance Criteria for Electric Railroad Facilities Based on Fuzzy TOPSIS

This paper is on the suggestion of maintenance items for electric railway facility systems.With the recent increase in the use of electric locomotives,the utilization and importance of railroad electrical facility systems are also increasing,but the railroad electrical facility system in Korea is rapidly aging.To solve this problem,various methodologies are applied to ensure operational reliability and stability for railroad electrical facility systems,but there is a lack of detailed evaluation criteria for railroad electrical facility system maintenance.Also,maintenance items must be selected in a scientific and systematic method.Therefore,railroad electrical facility systems are selected for study.Design StructureMatrix(DSM)is utilized to establish considerations tailored to the maintenance characteristics,and the Fuzzy-TOPSIS methodology is utilized for determining the maintenance detail evaluation item baseline weights,a multi-criteria decision-making problem.Studies show that degradation,insulation items have the highest weight of 14.63%,and capacity items have the lowest weight of 5.34%.The results of this may be contributed to the underlying research in carrying out maintenance activities to ensure the reliability and safety of railroad electrical facility systems.

Jam Formation of Traffic Flow in Harbor Tunnel

This paper reports a study concerning occurrence and growth of traffic jam in a harbor tunnel.The single-lane with three sections(downgrade,flat,and upgrade) is taken into account and they are characterized with different velocity limit.At the low density,the traffic current increases linearly with density and saturates at some values of immediately density.As the density increases,the traffic jam appears firstly before the upgrade section and then extends to the downgrade section.Additionally,the relationships of the velocity and headway against position in different densities are obtained from simulation.These results clearly clarify where and when the traffic jam appears. Finally,the critical densities are derived via the theoretical analysis before and after the discontinuous fronts and the theoretical results are consistent with the critical values of simulation results.

Zoning Search With Adaptive Resource Allocating Method for Balanced and Imbalanced Multimodal Multi-Objective Optimization

Maintaining population diversity is an important task in the multimodal multi-objective optimization.Although the zoning search(ZS)can improve the diversity in the decision space,assigning the same computational costs to each search subspace may be wasteful when computational resources are limited,especially on imbalanced problems.To alleviate the above-mentioned issue,a zoning search with adaptive resource allocating(ZS-ARA)method is proposed in the current study.In the proposed ZS-ARA,the entire search space is divided into many subspaces to preserve the diversity in the decision space and to reduce the problem complexity.Moreover,the computational resources can be automatically allocated among all the subspaces.The ZS-ARA is compared with seven algorithms on two different types of multimodal multi-objective problems(MMOPs),namely,balanced and imbalanced MMOPs.The results indicate that,similarly to the ZS,the ZS-ARA achieves high performance with the balanced MMOPs.Also,it can greatly assist a“regular”algorithm in improving its performance on the imbalanced MMOPs,and is capable of allocating the limited computational resources dynamically.

Object Detection for Cargo Unloading System Based on Fuzzy C Means

With the recent increase in the utilization of logistics and courier services,it is time for research on logistics systems fused with the fourth industry sector.Algorithm studies related to object recognition have been actively conducted in convergence with the emerging artificial intelligence field,but so far,algorithms suitable for automatic unloading devices that need to identify a number of unstructured cargoes require further development.In this study,the object recognition algorithm of the automatic loading device for cargo was selected as the subject of the study,and a cargo object recognition algorithm applicable to the automatic loading device is proposed to improve the amorphous cargo identification performance.The fuzzy convergence algorithm is an algorithm that applies Fuzzy C Means to existing algorithm forms that fuse YOLO(You Only Look Once)and Mask R-CNN(Regions with Convolutional Neuron Networks).Experiments conducted using the fuzzy convergence algorithm showed an average of 33 FPS(Frames Per Second)and a recognition rate of 95%.In addition,there were significant improvements in the range of actual box recognition.The results of this study can contribute to improving the performance of identifying amorphous cargoes in automatic loading devices.

A uniform framework of projection and community detection for one-mode network in bipartite networks

Projection is a widely used method in bipartite networks. However, each projection has a specific application scenario and differs in the forms of mapping for bipartite networks. In this paper, inspired by the network-based information exchange dynamics, we propose a uniform framework of projection. Subsequently, an information exchange rate projection based on the nature of community structures of a network(named IERCP) is designed to detect community structures of bipartite networks. Results from the synthetic and real-world networks show that the IERCP algorithm has higher performance compared with the other projection methods. It suggests that the IERCP may extract more information hidden in bipartite networks and minimize information loss.

Incentive regulation of banks on third party logistics enterprises in principal-agent-based inventory financing

In inventory financing,asymmetric information between banks and the third party logistics enterprises may incur moral risks,often causing economic losses of banks.To effectively solve this problem,a pure incentive scheme and a regulatory incentive scheme are designed with the principal-agent theory.By comparison,it is found that the pure incentive model is not applicable to practical conditions,and regulatory incentive model can not only solve practical problems substantially but also outbalance pure incentive model under certain conditions.The research results from example analysis given in this paper offer theoretical instruction and a practical method for effective regulation of banks.

Throughput Capacity of a Container Terminal Considering the Combination Patterns of the Types of Arriving Vessels

The throughput capacity of a container terminal is very important in planning and designing at container terminals.The existing methods estimated the throughput capacity without considering its change resulting from the different combination patterns of the types of arriving vessels.A simulation model is established to estimate the throughput capacities of a container terminal under different combination patterns of the types of arriving vessels.It shows that the throughput capacity of a container terminal is influenced by the utilization rates of the berth and quay cranes which result from the different combination patterns of the types of the arriving vessels.It provides a practical approach to estimate the throughput capacity of a container terminal considering the types of the vessels,and it is also helpful for the decision makers to raise the throughputs of the container terminals by optimizing the combination patterns of the types of arriving vessels.

Enhancing the Performance of JADE Using Two-phase Parameter Control Scheme and Its Application

The search efficiency of differential evolution(DE) algorithm is greatly impacted by its control parameters. Although many adaptation/self-adaptation techniques can automatically find suitable control parameters for the DE, most techniques are based on population information which may be misleading in solving complex optimization problems. Therefore, a self-adaptive DE(i.e., JADE) using two-phase parameter control scheme(TPC-JADE) is proposed to enhance the performance of DE in the current study. In the TPCJADE, an adaptation technique is utilized to generate the control parameters in the early population evolution, and a well-known empirical guideline is used to update the control parameters in the later evolution stages. The TPC-JADE is compared with four state-of-theart DE variants on two famous test suites(i.e., IEEE CEC2005 and IEEE CEC2015). Results indicate that the overall performance of the TPC-JADE is better than that of the other compared algorithms. In addition, the proposed algorithm is utilized to obtain optimal nutrient and inducer feeding for the Lee-Ramirez bioreactor. Experimental results show that the TPC-JADE can perform well on an actual dynamic optimization problem.

Alteration of pectin metabolism in blood orange fruit(Citrus sinensis cv.Tarocco)in response to vesicle collapse

Segment drying is a severe physiological disorder of citrus fruit,and vesicles become granulated or collapsed.Aside from the hypothesis that alteration of cell wall metabolism is the main factor of citrus granulation,little is known about vesicle collapse.This study aimed to elucidate the changes in pectin metabolism during vesicle collapse in blood orange.Vesicle collapse was characterized by decreased nutrients and increased chelate-and sodium carbonate-soluble pectin and calcium content.The nanostructure of chelate-soluble pectin became complex and developed multi-branching upon collapse.The activity of pectin methylesterase increased,while that of polygalacturonase and pectate lyase decreased upon collapse.Genome-wide transcriptional analysis revealed an increasing pattern of genes encoding pectin methylesterase and other enzymes involved in pectin synthesis and demethylesterification upon collapse.Drying vesicles were characterized by increased abscisic acid content and relevant gene expression.In conclusion,we discovered alteration in pectin metabolism underlying citrus vesicle collapse,mainly promoting pectin demethylesterification,remodeling pectin structures,and further inhibiting pectin degradation,which was hypothesized to be a main factor for citrus collapse.This is the first study to disclose the potential intrinsic mechanism underlying vesicle collapse in orange fruit.

A membrane-inspired algorithm with a memory mechanism for knapsack problems

Membrane algorithms are a class of distributed and parallel algorithms inspired by the structure and behavior of living cells. Many attractive features of living cells have already been abstracted as operators to improve the performance of algorithms. In this work, inspired by the function of biological neuron cells storing information, we consider a memory mechanism by introducing memory modules into a membrane algorithm. The framework of the algorithm consists of two kinds of modules (computation modules and memory modules), both of which are arranged in a ring neighborhood topology. They can store and process information, and exchange information with each other. We test our method on a knapsack problem to demonstrate its feasibility and effectiveness. During the process of approaching the optimum solution, feasible solutions are evolved by rewriting rules in each module, and the information transfers according to directions defined by communication rules. Simulation results showed that the performance of membrane algorithms with memory cells is superior to that of algorithms without memory cells for solving a knapsack problem. Furthermore, the memory mechanism can prevent premature convergence and increase the possibility of finding a global solution.