Adaptive Event-Based Consensus of Multi-Agent Systems with General Linear Dynamics

In this paper, adaptive event-based consensus of multi-agent systems with general linear dynamics is considered. A novel adaptive event-based controller and a state-dependent triggering function are proposed for each agent. The consensus can be achieved without the assumption that (A,B) is stabilizable. Furthermore, the Zeno-behavior of the concerned closed-loop system is also excluded under certain conditions. Finally, a numerical simulation example is presented to show the effectiveness of the theoretical results.     

An M/M/1 Queueing-Inventory System with Geometric Batch Demands and Lost Sales

This paper studies an M/M/1 queueing-inventory system with batch demands. Customers arrive in the system according to a compound Poisson process, where the size of the batch demands for each arrival is a random variable that follows a geometric distribution. The inventory is replenished according to the standard (s,S) policy. The replenishment time follows an exponential distribution. Two models are considered. In the first model, if the on-hand inventory is less than the size of the batch demands of an arrived customer, the customer takes away all the items in the inventory, and a part of the customer’s batch demands is lost. In the second model, if the on-hand inventory is less than the size of the batch demands of an arrived customer, the customer leaves without taking any item from the inventory, and all of the customer’s batch demands are lost. For these two models, the authors derive the stationary conditions of the system. Then, the authors derive the stationary distributions of the product-form of the joint queue length and the on-hand inventory process. Besides this, the authors obtain some important performance measures and the average cost functions by using these stationary distributions. The results are illustrated by numerical examples.     

Non-Monomial Permutations with Differential Uniformity Six

In this paper, a family of non-monomial permutations over the finite field \({F_{{2^n}}}\) with differential uniformity at most 6 is proposed, where n is a positive integer. The algebraic degree of these functions is also determined.     

Component ACD Model and Its Application in Studying the Price-Related Feedback Effect in Investor Trading Behaviors in Chinese Stock Market

This paper explores the investors’ feedback to the price change by modelling the price-related dynamics of trading intensity. A component decomposition duration modeling approach, called the component autoregressive conditional duration (CACD) model, is proposed to capture the variation of trading intensity across time intervals between price change events. Based on the CACD model, an empirical analysis is carried out on the Chinese stock market that covers different market statuses. The empirical results suggest that the CACD model can capture the price-related dynamics of trading intensity, which supports the existence of the feedback effect and is robust across different market statuses. The authors also study how the investors react to the price change by examining the driven factors of the price-related dynamics of trading intensity. The authors find that the trading can be triggered by the fast rise in the price level and the high trading volume. Besides, investors are more sensitive to the price change direction in the sideways market than in the upward or downward markets.     

An FE-Inexact Heterogeneous ADMM for Elliptic Optimal Control Problems with <Emphasis Type="Italic">L</Emphasis><Superscript>1</Superscript>-Control Cost

Elliptic PDE-constrained optimal control problems with L¹-control cost (L¹-EOCP) are considered. To solve L¹-EOCP, the primal-dual active set (PDAS) method, which is a special semismooth Newton (SSN) method, used to be a priority. However, in general solving Newton equations is expensive. Motivated by the success of alternating direction method of multipliers (ADMM), we consider extending the ADMM to L¹-EOCP. To discretize L¹-EOCP, the piecewise linear finite element (FE) is considered. However, different from the finite dimensional l1-norm, the discretized L¹-norm does not have a decoupled form. To overcome this difficulty, an effective approach is utilizing nodal quadrature formulas to approximately discretize the L¹-norm and L²-norm. It is proved that these approximation steps will not change the order of error estimates. To solve the discretized problem, an inexact heterogeneous ADMM (ihADMM) is proposed. Different from the classical ADMM, the ihADMM adopts two different weighted inner products to define the augmented Lagrangian function in two subproblems, respectively. Benefiting from such different weighted techniques, two subproblems of ihADMM can be efficiently implemented. Furthermore, theoretical results on the global convergence as well as the iteration complexity results o(1/k) for ihADMM are given. In order to obtain more accurate solution, a two-phase strategy is also presented, in which the primal-dual active set (PDAS) method is used as a postprocessor of the ihADMM. Numerical results not only confirm error estimates, but also show that the ihADMM and the two-phase strategy are highly efficient.     

Loading-Balance Relay-Selective Strategy Based on Stochastic Dynamic Program

A Relay-Assisted(RA) network with relay selection is considered as a type of effective technology to improve the spectrum and energy efficiency of a cellular network. However, loading balance of the assisted relay node becomes an inevitable bottleneck in RA network development because users do not follow uniform distribution. Furthermore, the time-varying channel condition of wireless communication is also a major challenge for the RA network with relay selection. To solve these problems and improve the practicability of the RA network, a Loading Balance-Relay Selective(LBRS) strategy is proposed for the RA network in this paper. The proposed LBRS strategy formulates the relay selection of the RA network under imperfect channel state information assumption as a Multistage Decision(MD) problem. An optimal algorithm is also investigated to solve the proposed MD problem based on stochastic dynamic program. Numerical results show that the performance of the LBRS strategy is better than that of traditional greedy algorithm and the former is effective as an exhaustive search-based method.     

Crystal-KMC: Parallel Software for Lattice Dynamics Monte Carlo Simulation of Metal Materials

Kinetic Monte Carlo(KMC) is a widely used method for studying the evolution of materials at the microcosmic level. At present, while there are many simulation software programs based on this algorithm, most focus on the verification of a certain phenomenon and have no analog-scale requirement, so many are serial in nature. The dynamic Monte Carlo algorithm is implemented using a parallel framework called SPPARKS, but it does not support the Embedded Atom Method(EAM) potential, which is commonly used in the dynamic simulation of metal materials. Metal material — the preferred material for most containers and components — plays an important role in many fields, including construction engineering and transportation. In this paper, we propose and describe the development of a parallel software program called Crystal-KMC, which is specifically used to simulate the lattice dynamics of metallic materials. This software uses MPI to achieve a parallel multiprocessing mode, which avoid the limitations of serial software in the analog scale. Finally, we describe the use of the parallel-KMC simulation software Crystal-KMC in simulating the diffusion of vacancies in iron, and analyze the experimental results. In addition, we tested the performance of Crystal-KMC in "meta-Era" supercomputing clusters, and the results show the Crystal-KMC parallel software to have good parallel speedup and scalability.     

Influence of strategy continuity on cooperation in spatial prisoner’s dilemma games with migrating players

The phenomenon of cooperation is prevalent in both nature and human society. In this paper a simulative model is developed to examine how the strategy continuity influences cooperation in the spatial prisoner’s games in which the players migrate through the success-driven migration mechanism. Numerical simulations illustrate that the strategy continuity promotes cooperation at a low rate of migration, while impeding cooperation when the migration rate is higher. The influence of strategy continuity is also dependent on the game types. Through a more dynamic analysis, the different effects of the strategy continuity at low and high rates of migration are explained by the formation, expansion, and extinction of the self-assembled clusters of “partial- cooperators” within the gaming population.     

Integrated heat and power dispatch model for wind-CHP system with solid heat storage device based on robust stochastic theory

This paper built a combined heat and power (CHP) dispatch model for wind-CHP system with solid heat storage device (SHS) aiming at minimizing system coal consumption, and set system demand-supply balance and units’ operation conditions as the operation constraints. Furthermore, robust stochastic optimization theory was used to describe wind power output uncertainty. The simulation result showed that SHS increased CHP peak-valley shifting capability and reduced abandoned wind rate from 12% to 6%, and reduced 5% coal consumption, compared with the original system operation by flexible charging electric power and heating. The payback period of employing SHS in wind-CHP system is far shorter than SHS expected service life.