Complexity analysis of the dual-channel supply chain model with delay decision

In the oligopoly e-commerce market, the oligarch retailers sell products through traditional channel, while others through both network and traditional channel in order to obtain greater profits. Instead of discussing classic Bertrand game model, which past studies have done, we considered dual-channel retailer who makes price decision through both in network channel and traditional channel. This paper used the bifurcation theory of dynamical system, considering dual-channel retailer who makes delay decision. We performed a numerical simulation on system with different conditions, and some complex phenomenons occured, such as bifurcation and chaos. The results showed that adopting price delay decision in tradition channel would make the system more stable. While, adopting price delay decision in network channel makes the system less stable. When the market is in chaotic state, the using of delay decision would have an effect on the system stability in either traditional or network channels. The system become stable from chaos and would return to chaotic again with the increasing of weight in past period. Some interesting phenomenons happened when dual-channel retailer adopted delay decision in both channels. The superposition of delay decision would make the system more complex. At last, we measured the system’s performance by using profit index. We analyzed the profits of different oligarchs when the system is in different states. When the system is in chaos, the total profits of the oligarchs are obviously less than that in a stable state. Adopting delay decision is a way to avoid profit loss when system is in chaotic period, but this requires the retailer has rich operational experience. That is because adopting delayed decision may not always enhance the competitive strength of oligarchs.     

Multi-objective optimization of the sandwich panels with prismatic cores using genetic algorithms

In the present study, a new type of sandwich panels with prismatic cores, which are capable of load bearing as well as cooling, is optimized to have minimum weight and maximum heat transfer performance. In order to simultaneously minimize the total weight and maximize the heat transfer performance, a multi-objective optimization approach has been developed using genetic algorithms. A set of compromised solutions, known as the tradeoff surface, is obtained. The tradeoff information between the two objectives is exploited in terms of multi-functionality of the sandwich panels, and the relation between the two objectives is quantified in the present study. The detailed configurations and dimensions of the sandwich panels at the optima are provided. Some basic characteristics of the sandwich panels with prismatic cores have been observed in terms of their multi-functionality.     

Decomposition optimization method for switching models using EM algorithm

This study proposes a decomposition optimization-based expectation maximization algorithm for switching models. The identities of each sub-model are estimated in the expectation step, while the parameters are updated using the decomposition optimization method in the maximization step. Compared with the traditional expectation maximization algorithm and the gradient descent expectation maximization algorithm, the decomposition optimization-based expectation maximization algorithm avoids the matrix inversion and eigenvalue calculation; thus, it can be extended to complex nonlinear models and large-scale models. Convergence analysis and simulation examples are given to show the effectiveness of the proposed algorithm.

     

Complex dynamics investigations of a mixed Bertrand duopoly game: synchronization and global analysis

Nonlinear Dynamics - In this paper, an economic competition between two firms that want to maximize the weighted-average social welfare and own profits is proposed. This kind of competition is...     

Research on the price game and the application of delayed decision in oligopoly insurance market

In the oligopoly insurance market, we assumed that some oligarchs make two-period delay decisions in bounded rationality and expectation, respectively, and others make decisions with bounded rationality without the condition of delay. There also exist two cases in which only one oligarch makes a delayed decision and two oligarchs make delayed decisions at the same time. Based on the analysis of these situations, we established the corresponding dynamic price game models. We then performed a numerical simulation to the complexity state of the system with different conditions such as stability, bifurcation, and chaos, and analyzed the profits of different oligarchs when the system is in different states. The results showed that when only one oligarch makes a delayed decision, with the decrease in the price weight of period t and increase in that of periods t?1 and t?2, the system??s stable region in the direction of the price adjustment of the oligarch with a delayed decision gets smaller. However, when there are two oligarchs with a delayed decision in the system, in the case where the delay parameters of oligarch 1 remain unchanged and the price parameters of different periods of oligarch 2 change, the system??s stable region in the direction of the price adjustment of oligarch 1 does not have the obvious change as that when only one oligarch makes a delayed decision. This showed that the sensibility of one oligarch in the direction of its own price adjustment is lower than other oligarchs. In addition, in the same system with delay and when the system is in chaos, the total profit of the oligarchs is obviously less than that when the system is in a stable state. However, the use of a delayed decision may not enhance the oligarch??s competitive advantages. Finally, the variable feedback control method is used to effectively control the chaos in the system.     

基于最优加权组合模型及高斯－牛顿法的滑坡变形预测研究

在对最优加权组合理论和高斯－牛顿法优化非线性模型参数的方法研究的基础上,依托于洒勒山滑坡的实际变形监测资料,建立了该滑坡变形预测的3个非线性预测模型：指数模型、Verhulst模型和灰色GM（1,1）模型;利用最优加权组合理论建立了洒勒山滑坡的最优加权组合预测模型,并运用高斯－牛顿法对各单一模型和组合模型的参数进行了优化。通过对比分析得出：组合模型的预测精度高于任何单一模型的预测精度;参数优化后各单一模型的预测精度都有不同程度的提高;参数优化后的组合模型预测精度是最高的。因此,综合运用最优组合理论和高斯－牛顿法处理滑坡预测预报模型,是提高滑坡预测预报精度的行之有效的方法。     

Speculative Price Dynamics in a Heterogeneous Agent Model

This paper proposes an agent model of financial markets and analyzes factors leading to speculative bubbles and speculative chaos of the asset price. A financial market is thought to contain two typical types of traders: fundamentalists and chartists who try to maximize their utility. It is shown that the nonlinearity of the excess demand functions, which are derived as a result of the traders' utility maximization, might generate speculative bubbles and speculative chaos of the asset price.     

Optimal Navier–Stokes Design of Compressor Impellers Using Evolutionary Computation

In the design of modern centrifugal compressor impellers, it is fundamental to account for three-dimensional effects and to use an optimization strategy that helps the designer to achieve the required objectives with the presence of constraints. In this paper, a fully three-dimensional optimization method is described that combines a CFD code and an evolutionary algorithm. The design scenario contemplated here involves the maximization of impeller peak efficiency with constraints on the impeller pressure ratio and operating range. The method is used to improve the performances of a baseline impeller of known characteristics. An optimal solution is proposed and compared to the original configuration.     

Effect of particle size distribution on particle based composite anode models

Particle based models of composite anodes are useful tools for exploring the behavior of SOFC systems. As part of our efforts to develop models for understanding fuel cells, we have been building models of Ni-YSZ composite anodes using experimentally measured particle size distributions. The objectives of this study were to characterize the percolation threshold and conductivity of these models in comparison to simpler mono dispersed and biphasic particle size distributions from the literature. We found that the average values for the onset of percolation and the measured conductivity of the models with experimentally measured particle size distributions are similar to those for the simple distributions and the experimentally measured distributions. For all of the configurations evaluated, the onset of percolation in the Nickel phase occurred at a solid fraction of Nickel between 20% and 25%. This corresponded almost exactly to the point at which the coordination number between Nickel phase particles reached 2.2. The significant finding was that the variation in the value for the conductivity, as measured by the standard deviation of the results, was several orders of magnitude higher than for the simpler systems. We explored the validity of our assumptions, specifically the assumption of random particle placement, by building a particle model directly from FIB-SEM data. In this reconstruction, it was clear that the location of particles was not random. Particles of the same type and size had much likelihood of contact higher than would indicated by random location.     

Optimization of a stepped circular pin-fin array to enhance heat transfer performance

A Stepped circular pin-fin array is formulated numerically and optimized with Kriging metamodeling technique to enhance heat transfer performance. The problem is defined by two non-dimensional geometric design variables composed of height of the channel, height of smaller diameter part of the pin-fins, and smaller diameter of the pin-fins, to maximize heat transfer rate compromising with friction loss. Ten designs generated by Latin hypercube sampling were evaluated by three-dimensional Reynolds-averaged Navier–Stokes solver and the evaluated objectives were used to construct the surrogate model. The predictions of objective function by Kriging model at optimum point show reasonable accuracy in comparison with the values calculated by RANS analysis. Optimum shape of pin-fins strongly depends on the weighting factor which measures importance of the friction loss term in the objective function. The thermal performances are much higher than that of the straight pin-fin at sampling optimum points with different weighting factors.     

Feasibility study on optimization of a typical solar chimney power plant

The solar chimney which has been built in Kerman (Kerman city-Iran) is a small scale electrical power plant. The chimney of this unit has 60 m height and 3 m diameter. The collector of this unit is 40 m × 40 m square. To reach nominal power of this unit of power plant, parameters which are effective in optimization are studied. In this regard, we deliberate and propose suggestions to maximize usage of solar energy and kinetic energy. The calculation of maximum power is one of the objectives of this study, so the paper present economic analysis for Kerman solar chimney. A home code has been written for this modeling, in MATLAB.     

Multi-objective optimization design of radar absorbing sandwich structure

By introducing a dimensionless parameter to couple the two objectives, weight and radar absorbing performance, into a single objective function, a multi-objective optimization procedure for the radar absorbing sandwich structure （RASS） with a cellular core is proposed. The optimization models considered are one-side clamped sandwich panels with four kinds of cores subject to uniformly distributed loads. The average specular reflectivity calculated with the transfer matrix method and the periodic moment method is utilized to characterize the radar absorbing performance, while the mechanical constraints include the facesheet yielding, core shearing, and facesheet wrinkling. The optimization analysis indicates that the sandwich structure with a two-dimensional （2D） composite lattice core filled with ultra-lightweight sponge may be a better candidate of lightweight RASS than those with cellular foam or hexagonal honeycomb cores. The 2D Kagome lattice is found to outperform the square lattice with respect to radar absorbing.     

Sensitivity‐guided decision‐making for wind farm micro‐siting

This paper presents a quantitative risk assessment for design and development of a renewable energy system to support decision‐making among design alternatives. Throughout the decision‐making phases, resources are allocated among exploration and exploitation tasks to manage the uncertainties in design parameters and to adapt designs to new information for enhanced performance. The resource allocation problem is formulated as a sequential decision feedback loop for a quantitative analysis of exploration and exploitation trade‐offs. We support decision‐making by tracking the evolution of uncertainties, the sensitivity of design alternatives to the uncertainties, and the performance, reliability, and robustness of each design. This is achieved by analyzing the uncertainties in the wind resource, the turbine performance and operation, and the models that define the power curve and wake deficiency. Comparison of the performance, reliability, and robustness of aligned and staggered turbine layouts before and after wind assessment experiments aids in improving micro‐siting decisions. The results demonstrate that design decisions can be supported by efficiently allocating resources towards improved estimates of achievable design objectives and by quantitatively assessing the risk in meeting those objectives. Copyright © 2016 John Wiley & Sons, Ltd.     

On a variant of the Maxwell and Oldroyd-B models within the context of a thermodynamic basis

In this paper we develop models within a thermodynamic standpoint that are very similar in form to the classical Maxwell and Oldroyd-B models but differ from them in one important aspect, the manner in which they unload instantaneously from the deformed configuration. As long as the response is not instantaneous, the models that are derived cannot be differentiated from the Maxwell and Oldroyd-B models, respectively. The models can be viewed within the context of materials whose natural configuration evolves, the evolution being determined by the maximization of the rate of entropy production of the material. However, the underpinnings to develop the model are quite different from an earlier development by Rajagopal and Srinivasa [8] in that while the total response of the viscoelastic fluid satisfies the constraint of an incompressible material, the energy storage mechanism associated with the elastic response is allowed to be that for a compressible elastic solid and the dissipative mechanism associated with the viscous response allowed to be that for a compressible fluid, the total deformation however being isochoric. The analysis calls for a careful evaluation of firmly held customs in viscoelasticity wherein it is assumed that it is possible to subject a material to a purely instantaneous elastic response without any dissipation whatsoever. Finally, while the model developed by Rajagopal and Srinivasa [8] arises from the linearization of the non-linear elastic response that they chose and leads to a model wherein the instantaneous elastic response is isochoric, here we develop the model within the context of a different non-linear elastic response that need not be linearized but the instantaneous elastic response not necessarily being isochoric.     

On the Design of Lifting Airfoils with High Critical Mach Number Using Full Potential Theory

 We wish to construct airfoils that have the highest free-stream Mach number for a given set of geometric constraints for which the flow is nowhere supersonic. Nonlifting airfoils that maximize the critical Mach number for a given cross-sectional area are known to possess long sonic segments at their critical speed. To construct lifting airfoils, we proceed under the conjecture that an airfoil with a high value of has the longest possible arc length of sonic velocity over its upper and lower surface. In Kropinski et al. (1995) the lifting problem was tackled in transonic small-disturbance theory. In this paper we numerically construct lifting airfoils with high using the full potential theory and we show that these airfoils have significantly higher than some standard airfoils. We also construct airfoils with higher values of the lift coefficient, by relaxing the speed constraint on the lower surface of the airfoil to have a value less than sonic. Received 13 May 1996 accepted 12 September 1996)     

Fluid–solid interaction simulation of flow and stress pattern in thoracoabdominal aneurysms: A patient-specific study

Thoracoabdominal aneurysm (TA) is a pathology that involves the enlargement of the aortic diameter in the inferior descending thoracic aorta and has risk factors including aortic dissection, aortitis or connective tissue disorders. Abnormal flow patterns and haemodynamic stress on the diseased aortic wall are thought to play an important role in the development of this pathology and the internal wall stress has proved to be more reliable as a predictor of rupture than the maximum diameter for abdominal aortic aneurysms; but this assumption has not been validated yet for aneurysms involving the thoracic aorta. In the present study, three patients with TAs of different maximum diameters were scanned using magnetic resonance imaging (MRI) techniques. Realistic models of the aneurysms were reconstructed from the in vivo MRI data acquired from the patients, and subject-specific flow conditions were applied as boundary conditions. The wall and thrombus were modelled as hyperelastic materials and their properties were derived from the literature. A normal descending aorta was also simulated to provide data for comparison. Fully coupled fluid–solid interaction (FSI) simulations as well as solid static simulations were performed using ADINA 8.2. The results show that the wall stress distribution and its magnitude are strongly dependent on the 3-D shape of the aneurysm and the distribution of thrombus. Maximum wall stresses in all TA models are higher than in the normal aorta, and values of maximum wall stress are not directly related to the maximum aneurysm diameter. Comparisons between the FSI and solid static simulation results showed no significant difference in maximum wall stress, supporting those previous studies which found that FSI simulations were not necessary for wall stress prediction.     

Analytical and computational modelling for wave energy systems: the example of oscillating wave surge converters

The development of new wave energy converters has shed light on a number of unanswered questions in fluid mechanics, but has also identified a number of new issues of importance for their future deployment. The main concerns relevant to the practical use of wave energy converters are sustainability, survivability, and maintainability. Of course, it is also necessary to maximize the capture per unit area of the structure as well as to minimize the cost. In this review, we consider some of the questions related to the topics of sustain-ability, survivability, and maintenance access, with respect to sea conditions, for generic wave energy converters with an emphasis on the oscillating wave surge converter. New analytical models that have been developed are a topic of par-ticular discussion. It is also shown how existing numerical models have been pushed to their limits to provide answers to open questions relating to the operation and characteristics of wave energy converters.     

Determining polymer molecular weight distributions from rheological properties using the dual-constraint model

Although multiple models now exist for predicting the linear viscoelasticity of a polydisperse linear polymer from its molecular weight distribution (MWD) and for inverting this process by predicting the MWD from the linear rheology, such inverse predictions do not yet exist for long-chain branched polymers. Here, we develop and test a method of inverting the dual-constraint model (Pattamaprom et al., Rheol Acta 39:517–531, 2000; Pattamaprom and Larson, Macromolecules 34:5229–5237, 2001), a model that is able to predict the linear rheology of polydisperse linear and star-branched polymers. As a first step, we apply this method only to polydisperse linear polymers, by comparing the inverse predictions of the dual-constraint model to experimental GPC traces. We show that these predictions are usually at least as good, or better than, the inverse predictions obtained from the Doi–Edwards double-reptation model (Tsenoglou, ACS Polym Prepr 28:185–186, 1987; des Cloizeaux, J Europhys Lett 5:437–442, 1988; Mead, J Rheol 38:1797–1827, 1994), which we take as a “benchmark”—an acceptable invertible model for polydisperse linear polymers. By changing the predefined type of molecular weight distribution from log normal, which has two fitting parameters, to GEX, which has three parameters, the predictions of the dual-constraint model are slightly improved. These results suggest that models that are complex enough to predict branched polymer rheology can be inverted, at least for linear polymers, to obtain molecular weight distribution. Further work will be required to invert such models to allow prediction of the molecular weight distribution of branched polymers.     

Attack robustness of cascading model with node weight

Considering the node weight and the effect of the neighboring nodes, we introduce a method to define the initial load of a node in a network and propose a cascading model. Our aim is to explore how to allocate the initial load and select some nodes to be protected so as to maximize the network robustness against cascading failures. According to the distribution of the node weight and the normalized effect of the neighboring nodes, we focus on investigating different roles of high-load and low-load nodes and the correlation between some parameters in our model and the strongest robust level of a network against cascading failures. We obtain by the numerical simulations the optimal values of the parameters in our model at which the network can reach the strongest robust level against cascading failures. In addition, we find that the effect of two attacks strongly depends on the parameters of the node weight and the normalized effect of the neighboring nodes, i.e., the network robustness of attacking the low-load nodes has a positive correlation with the parameter of the node weight, while has a negative correlation with the parameter of the normalized reaction of the neighboring nodes. While the result of attacking the high-load nodes is almost on the contrary. Finally, we verify the numerical results by the theoretical analysis.