The Energy Optimization Mathematic Algorithm on Multi-energy Resource Powertrain of Fuel Cell Vehicle

In order to solve the core issue of the energy regulation （ER） on multi-energy resource powertrain of fuel cell vehicle, the work functions of each component were defined; the mathematical algorithm model of energy regulation was established and the relevant solution was found. This algorithm was evaluated successfully on the hardware in loop （FILL） platform under three typical urban running cycles. The results showed ER control target had been realized and the mathematical algorithm was effective and reasonable. Based on the HIL simulation, some conclusions and ER strategies were made. According to the different power component parameters and real time control request, this algorithm should be modified and calibrated for application in the actual control system.

Modified Augmented Lagrange Multiplier Methods for Large-Scale Chemical Process Optimization

Chemical process optimization can be described as large-scale nonlinear constrained minimization. The modified augmented Lagrange multiplier methods (MALMM) for large-scale nonlinear constrained minimization are studied in this paper. The Lagrange function contains the penalty terms on equality and inequality constraints and the methods can be applied to solve a series of bound constrained sub-problems instead of a series of unconstrained sub-problems. The steps of the methods are examined in full detail. Numerical experiments are made for a variety of problems, from small to very large-scale, which show the stability and effectiveness of the methods in large-scale problems.

A Novel Particle Swarm Optimization for Flow Shop Scheduling with Fuzzy Processing Time

Since in most practical cases the processing time of scheduling is not deterministic, flow shop scheduling model with fuzzy processing time is established. It is assumed that the processing times of jobs on the machines are described by triangular fuzzy sets. In order to find a sequence that minimizes the mean makespan and the spread of the makespan, Lee and Li fuzzy ranking method is adopted and modified to solve the problem. Particle swarm optimization (PSO) is a population-based stochastic approximation algorithm that has been applied to a wide range of problems, but there is little reported in respect of application to scheduling problems because of its unsuitability for them. In the paper, PSO is redefined and modified by introducing genetic operations such as crossover and mutation to update the particles, which is called GPSO and successfully employed to solve the formulated problem. A series of benchmarks with fuzzy processing time are used to verify GPSO. Extensive experiments show the feasibility and effectiveness of the proposed method.

Analyzing the Relation Between Earthquakes and Active Faults Based on the Parameter Optimization Model

The gestation and occurrence of strong earthquakes are closely related to fault activity, which is not only revealed by abundant experimentation and seismism but also proved by modern seismology. On the Chinese mainland, the relation between earthquake activity and active faults is one of the bases for partitioning potential seismic sources, analyzing the seismotectoulcs and estimating location of strong earthquakes.Due to the nonuniformity of earth media, instability of observation systems and disturbance of the environment, etc, the variety of observational data is complicated, that is, there is no absolutely ＂normal＂ or ＂abnormal＂, and seismic anomalies can be divided into many mutually exdusive＂ abnormal states＂. In different conditions of combined time-spacestrength, determining seismic anomalies by different monomial forecast methods and its efficiency could be different due to the uncertainty of a precursor itself or complexity of the relationship between a precursor and earthquake gestation. It is very difficult to discover and dispose of this difference in actual application in a ＂two-state＂ model. But in a ＂multi-state＂ model, the difference can be easily reflected and the optimal combination of forecasting parameters for a forecast method can also be determined easily. Based on the ＂multi-state＂ precursory model and the optimization method for parameters of earthquake forecast model under the condition of optimal forecast efficiency, the relationship of the spatial location of earthquake with M ≥ 6.0 and active faults in three seismic belts are analyzed. The results demonstrate that in the Hetao Seismic Belt, seismicity is mostly concentrated in the range of 20 km along the fault, the optimization model can forecast the location of potential earthquakes of M ≥ 6.0 near the faults with a relatively high accuracy and the reliability is 0.5 ; while in the Qilian Mt. Seismic Belt, the reliability only reaches 0.14 when we use the model to estimate earthquakes within 30 km range along the faults. The ＂multi-state＂ precursory model, the efficiency-evaluating model and the parameter selection of individual earthquake forecast model based on optimal efficiency are of certain revelatory and practicable meanings for developing knowledge about precursors, investigating the laws of earthquake preparation and searching for optimal forecasting methods.

Liquid Flow Distribution in a New Type of Multi-tube Column

A new type of multi-tube column, in which a novel internal-structure is installed in the bed of random packing, has been invented. The internal-structure reduces the hydraulic radius of the column and adjusts the gas/liquid flow so that the liquid maldistribution is greatly abated. A mathematical model with boundary conditions based on close-open mechanism at the internal-structure was established to study the hydraulic behavior of such a column and experiments were carded out to verify the applicability of the model. Predictions from the model agreed well with experimental results. The optimal ratio of the hydraulic diameter of the new multi-tube column to the packing element diameter is found to be 17.5 to 23.3 by employing the optimization method of nonlinear programming. And this new type of multi-tube column opens a new way for random packing columns to be scaled up for industry.

Optimal Power Allocation for Heterogeneous Network Capacity Maximization

We investigate the optimal joint power allocation in Heterogeneous Networks （HetNets） to maximise its capacity. Consider- ing frequency reuse in the network, we study two power-constraint cases, i.e., per-cell po- wer constraint case and per-tier power con- straint case. We formulate the capacity maxi- mization problem by allowing each subcarrier of Marco eNodeB （MeNB） to be shared by users from multiple Picos. We mathematically demonstrate that the optimal power allocation in the per-cell power constraint case has a re- markably simple nature： each Pico transmits to its user with maximum power, while MeNB either selects only one user to jointly transmit with maximum power or does not transmit to any user. In the per-tier power constraint case, the difference is that the power allocation be- tween two Picos takes the form of water-fill- ing. Numerical results verify that our proposed schemes outperform the conventional interfe- rence coordination schemes.

Synthesis and optimization of utility system using parameter adaptive differential evolution algorithm

Synthesis and optimization of utility system usually involve grassroots design, retrofitting and operation optimization, which should be considered in modeling process. This paper presents a general method for synthesis and optimization of a utility system. In this method, superstructure based mathematical model is established, in which different modeling methods are chosen based on the application. A binary code based parameter adaptive differential evolution algorithm is used to obtain the optimal con figuration and operation conditions of the system. The evolution algorithm and models are interactively used in the calculation, which ensures the feasibility of con figuration and improves computational ef ficiency. The capability and effectiveness of the proposed approach are demonstrated by three typical case studies.

基于经济最优性与公平性的初始排污权免费分配模型

初始排污权的公开拍卖和标价出售这种有偿分配方式在实践中遇到阻力的情况下,学术界和实践中均认为免费分配更具有可操作性,但免费分配需要有一个参照基础或依据。给出一个基于经济最优性与公平性的初始排污权免费分配模型,并对该模型的性质进行了讨论。

A Group Testing Problem on a n- Item Set Containing Two Defective Ones

In this paper we study a group testing model ФX, Y,, XY. In other words, we consider a n-item set containing exactly two defective ones. The purpose of this paper is to find out the two defective items with a worst-case minimum number of tests, each of which will indicates whether the subset being tested contains all good （normal） items or not and in the latter case, it is not sure that the tested subset is of one defective （bad） item or two. Based on the M-sharp algorithm obtained in the previous paper and some combinatorial skills, we derive an almost optimal algorithm for the so called n-problem.