基于深度强化学习的深圳市急救车调度算法

在院前急救领域中,急救反应时间是指患者拨打急救电话后,急救车到达现场的时间。传统急救车调度算法未全面考虑急救环境的动态性和复杂性因素,导致模型优化的急救反应时间与实际情况存在偏差。将急救车调度问题建模成马尔科夫决策过程,构建基于深度强化学习的急救车调度算法。以多层感知机作为评分网络结构,通过将急救站的动态信息映射为各个急救站的得分,确定急救车被调往各急救站的概率。同时,结合急救车调度的动态决策特点,利用强化学习中演员-评论家框架下的近端策略优化算法改进评分网络参数。在深圳市急救中心真实急救数据集上的实验结果表明,相比Fixed、DSM、MEXCLP等算法,该算法在每个急救事件中的急救反应时间平均缩短约80 s,并且在10 min内急救车的平均到达比例为36.5%,能够实时地将急救车调度到合适的急救站。     

滚筒式采煤机煤岩截割力学特性及测试系统研究

为实现采煤机在煤岩截割过程中滚筒载荷受力的测试与分析,现场建立等比例大型采煤机力学特性分析研究实验平台,采用等效结构惰轮轴传感器测试方法,针对滚筒式采煤机在煤岩截割过程中采煤机滚筒载荷变化进行实时动态在线监测,采用无线信号发射装置实现测试数据的实时传输。现场截割实验结果表明,在采煤机截割煤岩过程中,滚筒x,y,z三向上的载荷峰值差分别为29.941,17.459和7.371kN,载荷变化显著,测试结果符合现场实际工况,为实现采煤机煤岩动态识别以及自动调高控制提供了重要的理论和数值依据。     

Reprogrammable Assembly of Molecular Motor on Solid Surfaces via Dynamic Bonds

Controllable assembly of molecular motors on solid surfaces is a fundamental issue for providing them to perform physical tasks. However, it can hardly be achieved by most previous methods due to their inherent limitations. Here, a general strategy is designed for the reprogrammable assembly of molecular motors on solid surfaces based on dynamic bonds. In this method, molecular motors with disulfide bonds can be remotely, reversibly, and precisely attached to solid surfaces with disulfide bonds, regardless of their chemical composition and microstructure. More importantly, it not only allows encoding geometric information referring to a pattern of molecular motors, but also enables erasing and re‐encoding of geometric information via hemolytic photocleavage and recombination of disulfide bonds. Thus, solid surfaces can be regarded as “computer hardware”, where molecular motors can be reformatted and reprogramed as geometric information.     

Joint pricing and advertising strategy with reference price effect

Consumers are susceptible to reference price effects when they make purchase decisions for a certain product. Meanwhile, the sales price and advertisement are the determinable factors that have impact on consumers’ reference price which are also fundamental marketing strategies. Therefore, how to determine an appropriate sales price and advertising effort level to maximise firms’ profits is an essential task. A joint pricing and advertising problem for a monopolistic firm with consideration of reference price effect is investigated, where consumer demand rate is price-sensitivity and depends on the gap between the sales price and the reference price in consumers’ mind. An optimisation model is established to maximise the firm’s total profit by making a joint pricing and advertising strategy. The static and dynamic joint strategies are obtained by applying Pontryagin’s maximum principle. Results show that the dynamic strategies dominate the static ones. Furthermore, the dynamic pricing and dynamic advertising strategies are strategic complements. Additionally, the length of the sales period plays a key role in determining the superiority of the two dynamic strategies. Specifically, a relatively short sales period highlights the value of the dynamic advertising while a long sales period strengthens the function of the dynamic pricing.     

Myopic vs. far-sighted behaviours in a revenue-sharing supply chain with reference quality effects

In this paper, we consider a dynamic supply chain where a manufacturer produces and distributes a featured product through an exclusive retailer to end consumers. The manufacturer decides the product quality and wholesale price, while the retailer sets the retail price in the presence of a revenue-sharing contract and consumers’ reference quality effects. The objective of this study is to investigate the impacts of myopic behaviour regarding the reference quality on the product quality and pricing strategies and profits of both members. Our results suggest that the manufacturer’s myopia leads to a higher quality, higher price strategy and a higher quality–price ratio which benefits consumers. Meanwhile, relative to the far-sighted behaviour, myopia results in a more quality-sensitive but less price-sensitive market demand. What’s more, we find that the manufacturer is apt to act in a far-sighted way, but the retailer isn’t always willing to cooperate with a far-sighted manufacturer. Taking myopic strategies for both members is likely to gain a high profit of the whole supply chain for a relatively high marginal contribution of product quality on demand and a relatively low revenue-sharing proportion.     

Optimal markdown policy of perishable food under the consumer price fairness perception

Markdown policies are widely used by retailers to sell perishable food. Consumers purchase food at different prices during different sales periods. Some consumers may compare their experience with others who purchase the same items. Price unfairness or inequity is perceived when different prices are quoted without reasonable explanations. This study develops an optimal markdown model for perishable food pricing to optimise the food retailer revenue and enable a maximum aggregated consumer utility considering individuals’ price fairness perception. The model serves as the first step in evaluating trade-offs between food retailer revenue and consumer utility. In addition, it enables consumer utility to be depicted through perceived price fairness by including the effects of food perishability and scarcity. Another innovative feature is the equalisation of the consumer average aggregated utility during different sales periods as a condition of intertemporal price fairness perception. The proposed model is compared with two benchmark models to justify the effectiveness and advantages in the example. Finally, a sensitive analysis based on the food deterioration rate, consumer food desire rate and consumer average reservation price is conducted to justify the manner in which these factors influence the optimal pricing policy, and managerial insights are suggested for food retailers.     

Online hot selling period and its impact on e-retailer’s pricing strategies

The express delivery industry is often overloaded in some hot online selling seasons, which causes consumers’ dissatisfaction. Under such a circumstance, the e-retailer can utilise two opposite strategies, i.e. to set-up either a low price with a pre-announced markdown pricing (PMDP) strategy, or a high price with a pre-announced markup pricing (PMUP) strategy for the hot selling period. As both the prices and the express service quality are different between the regular period and the hot selling period, consumers can strategically choose their purchase time, which will in turn influences the e-retailer’s pricing strategy. To investigate under what condition one pricing strategy will dominate the other, we propose a two period pricing model in which the selling season are divided into regular and hot selling period, and all consumers are assumed to be strategic. The e-retailer determines the prices over the two kinds of periods to maximise its profit. The comparison shows that a PMUP (resp. PMDP) strategy is preferred when the overloading degree in the hot selling period is slight (resp. heavy). Furthermore, we extend our model by incorporating the competition of traditional retailers.     

A mathematical model for vehicle routing problem under endogenous uncertainty

In this study, a multistage stochastic programming (SP) model is presented for a variant of single-vehicle routing problem with stochastic demands from a dynamic viewpoint. It is assumed that the actual demand of a customer becomes known only when the customer is visited. This problem falls into the category of SP with endogenous uncertainty and hence, the scenario tree is decision-dependent. Therefore, nonanticipativity of decisions is ensured by conditional constraints making up a large portion of total constraints. Thus, a novel approach is proposed that considerably reduces the problem size without any effect on the solution space. Computational results on some test problems are reported.     

Strain Rate Effects on Dynamic Fractures in Fine‐grained Granitic Rock

The effect of dynamic strain rates on failure responses of a fine‐grained granitic rock is studied experimentally and theoretically. Theoretical investigation employs a model incorporating dynamic fracture criterion with damage mechanics theory. Experimental investigation is conducted using split Hopkinson pressure bar device. In order to investigate the effects of microstructure on dynamic fracture failure under different loading rates, fragment debris of each tested specimen is collected and analyzed. It is found through the debris analysis that the granitic rock breaks down into the fragment debris in grain size scales and the effect of strain rates on the formation of fragment debris appears to be related to the microstructure of the rock. It is also found that dynamic inertia induced by the dynamic loading can reduce the effect of friction confinement generated by the contact between the cylindrical specimen and two split Hopkinson pressure bars on the dynamic responses of the specimen. Theoretical evaluations agree with the corresponding experimental observations.     

Dynamic flow‐based particle splitting in smoothed particle hydrodynamics

In this work, a dynamic procedure for local particle refinement to be used in smoothed particle hydrodynamics (SPH) is presented. The algorithm is able to consistently produce successive levels of particle splitting in accordance to a flow‐based criterion. It has been applied together with accurate and robust formulations for variable spatial resolution in the framework of a semi‐implicit, truly incompressible scheme for SPH. Different test cases have been considered to assess the capabilities and advantages of the proposed procedure, namely, the laminar flow around circular and square obstacles in a plane channel for various regimes. Such flow cases entail the simulation of attached and separated shear layers, recirculating flow, vortex shedding and surface discontinuities. The results obtained for two levels of particle splitting have demonstrated that significant improvements may be obtained with respect to uniform particle spacing solutions in a variety of situations, thus presenting an excellent trade‐off between accuracy and computational cost. Copyright © 2015 John Wiley & Sons, Ltd.