Open dynamic behaviour of financial markets

Open dynamic behaviour of financial markets with internal interactions between agents and with external “fields” from other systems are investigated using the approach of Grossman and Stiglitz for inefficient markets, and Keynes for interference of the market using physics of finance (referred to hereafter as phynance). The simulation results indicate that the NYSE data analyzed in Plerou, V. et al., Nature 421, 130 (2003) can be fitted by an equation of order parameter Φ and local deviation R of type: -(R+0.03) Φ+ 0.6 Φ³ + 0.02 = 0, which is shown to be in remarkable agreement with Plerou's data.     

Deterministic impulse control in native forest ecosystems management

This paper illustrates an application of impulse control systems analysis to the management of renewable resources. We obtain an explicit definition for the impulse optimal strategy in the case of a nonlinear natural system which models certain types of forests. The result is in agreement with an econo-ecological conservative action on the forest. The examples developed in this paper associate new theories on impulse or jump control with natural forest management. In addition, we compare our results with the classical ones. We also show that a nonoptimal managing action on the forest is frequently the cause for significant medium-term losses.This work was supported by CONICET, Consejo Nacional de Investigaciones Científicas y Técnicas, and by the Universidad Nacional del Litoral, Argentina.     

Active Inference: Applicability to Different Types of Social Organization Explained through Reference to Industrial Engineering and Quality Management

Active inference is a physics of life process theory of perception, action and learning that is applicable to natural and artificial agents. In this paper, active inference theory is related to different types of practice in social organization. Here, the term social organization is used to clarify that this paper does not encompass organization in biological systems. Rather, the paper addresses active inference in social organization that utilizes industrial engineering, quality management, and artificial intelligence alongside human intelligence. Social organization referred to in this paper can be in private companies, public institutions, other for-profit or not-for-profit organizations, and any combination of them. The relevance of active inference theory is explained in terms of variational free energy, prediction errors, generative models, and Markov blankets. Active inference theory is most relevant to the social organization of work that is highly repetitive. By contrast, there are more challenges involved in applying active inference theory for social organization of less repetitive endeavors such as one-of-a-kind projects. These challenges need to be addressed in order for active inference to provide a unifying framework for different types of social organization employing human and artificial intelligence.     

Enhancing light absorption for organic solar cells using front ITO nanograting and back ultrathin Al layer

To address the discrepancy between carrier collection and light absorption of organic solar cells caused by the limited carrier mobility and optical absorption coefficient for the normally employed organic photoactive layers, a light management structure composed of a front indium tin oxide(ITO) nanograting and ultrathin Al layer inserted in between the photoactive layer and the electron transport layer(ETL) is introduced. Owing to the antireflection and light scattering induced by the ITO nanograting and the suppression of light absorption in the ETL by the inserted Al layer, the light absorption of the photoactive layer is significantly enhanced in a spectral range from 400 nm to 650 nm that also covers the main energy region of solar irradiation for the normally employed active materials such as the P3HT:PC_(61) BM blend. The simulation results indicate that comparing with the control device with a planar configuration of ITO/PEDOT:PSS/P3HT:PC_(61) BM(80-nm thick)/Zn O/Al, the short-circuit current density and power conversion efficiency of the optimized light management structure can be improved by 32.86% and 34.46%. Moreover, good omnidirectional light management is observed for the proposed device structure. Owing to the fact that the light management structure possesses the simple structure and excellent performance, the exploration of such a structure can be believed to be significant in fabricating the thin film-based optoelectronic devices.     

APPLICATION OF VARIABLE-FIDELITY MODELS TO AERODYNAMIC OPTIMIZATION

For aerodynamic shape optimization, the approximation management framework (AMF) method is used to organize and manage the variable-fidelity models. The method can take full advantage of the low-fidelity, cheaper models to concentrate the main workload on the low-fidelity models in optimization iterative procedure. Furthermore, it can take high-fidelity, more expensive models to monitor the procedure to make the method globally convergent to a solution of high-fidelity problem. Finally, zero order variable-fidelity aerodynamic optimization management framework and search algorithm are demonstrated on an airfoil optimization of UAV with a flying wing. Compared to the original shape, the aerodynamic performance of the optimal shape is improved. The results show the method has good feasibility and applicability.     

Manufacturer’s revenue-sharing contract and retail competition

This paper investigates a revenue-sharing contract for coordinating a supply chain comprising one manufacturer and two competing retailers. The manufacturer, as a Stackelberg leader, offers a revenue-sharing contract to two competing retailers who face stochastic demand before the selling season. Under the offered contract terms, the competing retailers are to determine the quantities to be ordered from the manufacturer, prior to the season, and the retail price at which to sell the items during the season. The process of pricing and ordering is expected to result in an equilibrium as in the Bayesian Nash game. On the basis of anticipated responses and actions of the retailers, the manufacturer designs the revenue-sharing contract. Adopting the classic newsvendor problem model framework and using numerical methods, the study finds that the provision of revenue-sharing in the contract can obtain better performance than a price-only contract. However, the benefits earned under the revenue-sharing contract by different supply chain partners differ because of the impact of demand variability and price-sensitivity factors. The paper also analyses the impact of demand variability on decisions about optimal retail price, order quantity and profit sharing between the manufacturer and the retailers. Lastly, it investigates how the competition (between retailers) factor influences the decision-making of supply chain members in response to uncertain demand and profit variability.     

高功率光纤激光器二级抽运技术的理论分析

从理论上分析了高功率光纤激光器直接抽运和二级抽运的斜率效率和热管理问题. 计算结果表明:波长为975 nm的激光直接抽运产生波长为1070 nm的激光时,理论斜率效率为80%,但当抽运光功率为10 kW时,在强制水冷条件下纤芯极值温度也难以降到150 ℃以下;在二级抽运技术中,波长为1018 nm的激光抽运产生波长为1070 nm的激光时,若采用传统的包层抽运技术,其斜率效率不足20%,如果抽运功率填充因子由0.0025提高到0.1,则理论上斜率效率可由18.5%提高到80.9%,从而总斜率效率由15.5 关键词： 二级抽运 功率填充因子 斜率效率 热管理     

Dynamic pricing inventory control under fixed cost and lost sales

This paper studies a periodic review pricing and inventory replenishment problem which encounters stochastic demands in multiple periods. In many inventory control problems, the unsatisfied demand is traditionally assumed to be backlogged but in this paper is assumed to be lost. In many practical problems, a consumer who could not buy what he/she wants in one store is not willing to wait until that store restocks it but tries to buy alternatives in other stores. Also, in this paper, the random variable for the demand function is assumed to be general, which means that any probability function for the random variable can be applied to our result. Cost terms consist of the holding cost by the leftover, the shortage cost by lost sales, and the strictly positive fixed ordering cost. The objective of this paper is to dynamically and simultaneously decide the optimal selling price and replenishment in each period by maximizing the expected profit over the finite selling horizon. We show that, under the general assumption on the random variable for the demand, the objective function is K$K$-concave, an (s,S)$(s\text{,}S)$ policy is optimal for the replenishment and the optimal price is determined based on the inventory level after the replenishment in each period.     

Timing and eco(nomic) efficiency of climate-friendly investments in supply chains

Emission trading schemes such as the European Union Emissions Trading System (EUETS) attempt to reconcile economic efficiency with ecological efficiency by creating financial incentives for companies to invest in climate-friendly innovations. Using real options methodology, we demonstrate that under uncertainty, economic and ecological efficiency continue to be mutually exclusive. This problem is even worse if a climate-friendly project depends on investing in of a whole supply chain. We model a sequential bargaining game in a supply chain where the parties negotiate over implementation of a carbon dioxide (CO₂) saving investment project. We show that the outcome of their bargaining is not economically efficient and even less ecologically efficient. Furthermore, we show that a supply chain becomes less economically efficient and less ecologically efficient with every additional chain link. Finally, we make recommendations for how managers or politicians can improve the situation and thereby increase economic as well as ecological efficiency and thus also the eco-efficiency of supply chains.     

On the cooperation of recycling operations

This paper addresses two important issues that may affect the operations efficiency in the recycling industry. First, the industry contains many small-scale and inefficient recycling firms, especially in developing countries. Second, the output from recycling a waste product often yields multiple recycled products that cannot all be sold efficiently by a single firm. To address these two issues, this paper examines how different firms can cooperate in their recycling and pricing decisions using cooperative game theory. Recycling operations under both joint and individual productions with different cost structures are considered. Decisions include the quantity of waste product to recycle and the price at which to sell each recycled product on each firm’s market. These decisions can be made jointly by multiple cooperating firms to maximize total profit. We design allocation schemes for maximized total profit to encourage cooperation among all firms. Managerial insights are provided from both environmental and economic perspectives.