THE ANALYSIS OF THE SEPARATED LAYERS ALGORITHM BY DOMAIN DECOMPOSITION METHOD

From the principle of of the Domain Decomposition Method (DDM), we analyse the 2nd-order linear elliptic partial differential problems and link the Separated-Layers Algorithm (SLA) with DDM. The mathematical properties of SLA and numerical example are presented to obtain satisfactory computation results. For general linear differential ones, also are the structure of SLA and its characteristics discussed.     

Simultaneous solving of balancing and sequencing problems with station-dependent assembly times for mixed-model assembly lines

In spite of many studies, investigating balancing and sequencing problems in Mixed-Model Assembly Line (MMAL) individually, this paper solves them simultaneously aiming to minimize total utility work. A new Mixed-Integer Linear Programming (MILP) model is developed to provide the exact solution of the problem with station-dependent assembly times. Because of NP-hardness, a Simulated Annealing (SA) is applied and compared to the Co-evolutionary Genetic Algorithm (Co-GA) from the literature. To strengthen the search process, two main hypotheses, namely simultaneous search and feasible search, are developed contrasting Co-GA. Various parameters of SA are reviewed to calibrate the algorithm by means of Taguchi design of experiments. Numerical results statistically show the efficiency and effectiveness of the proposed SA in terms of both the quality of solution and the time of achieving the best solution. Finally, the contribution of each hypothesis in this superiority is analyzed.     

Multidisciplinary optimization of gas-quenching process

Distortion as a result of the quenching process is predominantly due to the thermal gradient and phase transformations within the component. Compared with traditional liquid quenching, the thermal boundary conditions during gas quenching are relatively simple to control. By adjusting the gas-quenching furnace pressure, the flow speed, or the spray nozzle configuration, the heat-transfer coefficients can be designed in terms of both the component geometry and the quenching time. The purpose of this research is to apply the optimization methodology to design the gas-quenching process. The design objective is to minimize the distortion caused by quenching. Constraints on the average surface hardness, and its distribution and residual stress are imposed. The heat-transfer coefficients are used as design variables. DEFORM-HT is used to predict material response during quenching. The response surface method is used to obtain the analytical models of the objective function and constraints in terms of the design variables. Once the response surfaces of the objective and constraints are obtained, they are used to search for the optimum heat-transfer coefficients. This process is then used instead of the finite-element analysis. A one-gear blank case study is used to demonstrate the optimization scheme.     

水性聚氨酯材料配方设计技巧

介绍了优选法的0.618法和分数法,对其进行改进创新和原理证明,并应用于生产涂料配方设计中。     

Cross-evaluation-based weighted linear optimization for multi-criteria ABC inventory classification

Multi-criteria ABC inventory classification (MCIC), which aims to classify inventory items by considering more than one criterion, is one of the most widely employed techniques for inventory control. This paper suggests a cross-evaluation-based weighted linear optimization (CE-WLO) model for MCIC that incorporates a cross-efficiency evaluation method into a weighted linear optimization model for finer classification (or ranking) of inventory items. The present study demonstrated the inventory-management-cost effectiveness and advantages of the proposed model using a simulation technique to conduct a comparative experiment with the previous, related investigations. We established that the proposed model enables more accurate classification of inventory items and better inventory management cost effectiveness for MCIC, specifically by mitigating the adverse effect of flexibility in the choice of weights and yielding a unique ordering of inventory items.     

Recommending suitable learning scenarios according to learners’ preferences: An improved swarm based approach

The paper presents a new approach for recommending suitable learning paths for different learners groups. Selection of the learning path is considered as recommendations to choosing and combining the sequences of learning objects (LOs) according to learners’ preferences. Learning path can be selected by applying artificial intelligence techniques, e.g. a swarm intelligence model. If we modify and/or change some LOs in the learning path, we should rearrange the alignment of new and old LOs and reallocate pheromones to achieve effective learning recommendations. To solve this problem, a new method based on the ant colony optimisation algorithm and adaptation of the solution to the changing optimum is proposed. A simulation process with a dynamic change of learning paths when new LOs are inserted was chosen to verify the method proposed. The paper contributes with the following new developments: (1) an approach of dynamic learning paths selection based on swarm intelligence, and (2) a modified ant colony optimisation algorithm for learning paths selection. The elaborated approach effectively assist learners by helping them to reach most suitable LOs according to their preferences, and tutors – by helping them to monitor, refine, and improve e-learning modules and courses according to the learners’ behaviour.     

富集均三甲苯塔的模拟与优化

在满足工艺要求的基础上，通过富集均三甲苯塔模拟与优化给出最佳操作条件，用于指导实际操作和设备改造．优化生产参数。     

Consistent hierarchical economic NMPC for a class of hybrid systems using neighboring-extremal updates

A hierarchical two-layer control algorithm is developed for a class of hybrid (discrete-continuous dynamic) systems to support economically optimal operation of batch or continuous processes with a predefined production schedule. For this class of hybrid systems, the optimal control moves as well as the controlled switching times between two adjacent modes are determined online. In contrast to closely related schemes for integrated scheduling and control, the sequence of modes is not optimized. On the upper layer, the economic optimal control problem is solved rigorously by a slow hybrid economic model predictive controller at a low sampling rate. On the lower layer, a fast hybrid neighboring-extremal controller is based on the same economic optimal control problem as the slow controller to ensure consistency between both layers. The fast neighboring-extremal controller updates rather than tracks the optimal trajectories from the upper layer to account for disturbances. Consequently, the fast controller steers the process to its operational bounds under disturbances and the economic potential of the process is exploited anytime. The suggested two-layer control algorithm provides fully consistent control action on the fast and slow time-scale and thus avoids performance degradation and even infeasibilities which are commonly encountered if inconsistent optimal control problems are formulated and solved.     

化工搅拌器的参数优选

本文提出了确定化工用搅拌器搅拌时间的一种简单试验方法,并用正交表安排寻找最佳搅拌参数的试验和整理试验数据,得到了有实用价值的结果。     

An analysis,design and tuning of Cascade Control Systems in the presence of constraints in actuator and process outputs

In the presence of rate constraints in actuator, design of cascade controller based on the primary controller conditional integration can result into closed-loop system oscillations. Stability analysis, performed by the describing function technique and confirmed by simulation, demonstrates that the solution based on the Anti-Reset Windup Cascade Control System (ARW CCS) structure is successful. Design and tuning of the ARW CCS secondary controller is a standard ARW single-input single-output problem. In the present paper tuning is proposed for the ARW CCS primary controller. For the serial process modeling simple rules are derived and confirmed by experimental results, obtained on a drum type boiler of a 210 MWe lignite coal fired unit. General design of the ARW CCS is based on the parallel process modeling and optimization of the primary controller. Optimization is performed in the frequency domain, under constraints on the maximum sensitivity, multiplicative uncertainty bound and sensitivity to measurement noise. Simulation and experimental results on a laboratory thermal plant demonstrate effectiveness of the proposed optimization.