Geographical characterisation of honeys according to their mineral content and antioxidant activity using a chemometric approach

In this article, discrimination models are presented, relating the origin of honey samples to several variables, being the concentrations of different cations and anions in the honey samples measured by ion chromatography, and parameters that measure/reflect the antioxidant activity of the honey samples. The unsupervised method, principal component analysis, and supervised discrimination methods, such as linear and quadratic discriminant analysis, and classification and regression trees (CART), were applied to evaluate the existence of data patterns and the relationship between geographical origin and the measured parameters. The model with the best predictive ability (%CCR_TEST = 66.67%), the best overall % specificity (80%) and the best overall % sensitivity (67%) was found to be CART. It was proven that the mineral content and parameters analysed can provide enough information for the geographical characterisation and discrimination of honey.     

Design and analysis of an aging‐aware energy management system for islanded grids using mixed‐integer quadratic programming

The rapid increase of renewable energy sources made coordinated control of the distributed and intermittent generation units a more demanded task. Matching demand and supply is particularly challenging in islanded microgrids. In this study, we have demonstrated a mixed‐integer quadratic programming (MIQP) method to achieve efficient use of sources within an islanded microgrid. A unique objective function involving fuel consumption of diesel generator, degradation in a lithium‐ion battery energy storage system, carbon emissions, load shifting, and curtailment of the renewable sources is constructed, and an optimal operating point is pursued using the MIQP approach. A systematic and extensive methodology for building the objective function is given in a sequential and explicit manner with an emphasis on a novel model‐based battery aging formulation. Performance of the designed system and a sensitivity analysis of resulting battery dispatch, diesel generator usage, and storage aging against a range of optimization parameters are presented by considering real‐world specifications of the Semakau Island, an island in the vicinity of Singapore.     

开缝衬套挤压工艺影响TA15孔疲劳增益研究

采用对比疲劳试验方法,研究了相对挤压量、终铰参量、衬套开缝放置角度等工艺参数和特征对开缝衬套挤压TA15钛合金连接孔疲劳增益的影响。结果表明,开缝衬套挤压技术可有效提高TA15钛合金孔结构疲劳强度,延长其疲劳寿命；相对挤压量越大,孔挤压疲劳增益越大,但是TA15钛合金对挤压量非常敏感,微小的相对挤压量波动会导致显著的疲劳增益波动；在完全去除开缝衬套在孔壁遗留的材料凸脊前提下,0.190 mm和0.065 mm两种单边终铰参量对TA15孔结构挤压疲劳增益有明显影响,0.190 mm单边铰削量时挤压疲劳增益更大,而非终铰参量越小越好；在s_max=400 MPa,R=0.1疲劳载荷条件下,衬套开缝与试样最窄截面平行放置,仍能够获得明显的疲劳增益,但相对于与试样与最窄截面呈90°放置,疲劳增益会略有下降,建议在实际孔挤压操作中,衬套开缝尽量避开最窄截面放置。     

Seqential approach in job shop scheduling

Abstract

This study investigats a new approach‐the sequential approach‐ in job shop scheduling. The objective is to minimize the total of lateness cost and set‐up cost in job shops. Whenever a scheduling decision has to be made as to which job should receive the next processing, this approach considers each cost sequentially. One of the two costs is considered first, and every time all waiting jobs must be examined in terms of this cost, and only those jobs qualified would the second cost apply to and from which a job would be selected for processing. This investigation was carried out by using GASP IV simulation under a variety of job shop situations. The effectiveness of this approach and job selection mechanism constitute the main theme of this study.     

Flight path optimization passing through waypoints for autonomous flight control systems

Trajectory optimization is performed to generate a flight path passing specified waypoints. To deal with the unspecified time of passing through a waypoint, an auxiliary variable is introduced. Normalization of the time variable by the auxiliary variable transforms the waypoint optimization problem into the conventional optimization problem. The condition for passing through the waypoints can be relaxed, so that the vehicle passes specified waypoints within a certain acceptable range. Sequential quadratic programming is used to solve the optimization problem. As a numerical example, six degree-of-freedom vehicle dynamics is considered. Two-dimensional and three-dimensional trajectory optimization problems with several waypoints are solved to verify the effectiveness of the proposed algorithm.     

Optimal allocation of phasor measurement unit for full observability of the connected power network

This paper presents binary particle swarm optimization (BPSO) technique for the optimal allocation of phasor measurement units (PMUs) for the entire observability of connected power network. Phasor measurement units are considered as one of the most important measuring devices in the prospect of connected power network. PMUs function may be incorporated to the wide-area connected power networks for monitoring and controlling purposes. The optimal PMU placement (OPP) problem provides reference to the assurance of the minimal number of PMUs and their analogous locations for observability of the entire connected power networks. Binary particle swarm optimization (BPSO) algorithm is developed for the solution of OPP problem. The efficacy and robustness of the proposed method has been tested on the IEEE 14-bus, IEEE 30-bus, New England 39-bus, IEEE 57-bus, IEEE 118-bus and Northern Regional Power Grid (NRPG) 246-bus test system. The results obtained by proposed approach are compared with other standard methods and it is observed that this BPSO based placement of phasor measurement units is found to be the best among all other techniques discussed.     

Optimal Location of Unified Power Quality Conditioner in Distribution System for Power Quality Improvement

The increased use of nonlinear loads in distribution system is increasing the distortion in the voltage and current waveforms. Moreover, the distribution systems are inherently unbalanced. This paper presents Cuckoo Optimization Algorithm (COA) based Unified Power Quality Conditioner (UPQC) allocation in three phase unbalanced distribution network. The performance of UPQC is studied in terms of minimization of load disturbance during fault condition in the test systems, % reduction of total harmonic distortion and individual harmonics, minimization of real power loss, decrease in voltage unbalance and increase in cost savings during normal operating condition. The performance of COA is compared with other soft computing techniques to get the better results, i.e., better voltage profile, the optimal location and optimal number of UPQCs.     

Metaheuristics for the single machine weighted quadratic tardiness scheduling problem

This paper considers the single machine scheduling problem with weighted quadratic tardiness costs. Three metaheuristics are presented, namely iterated local search, variable greedy and steady-state genetic algorithm procedures. These address a gap in the existing literature, which includes branch-and-bound algorithms (which can provide optimal solutions for small problems only) and dispatching rules (which are efficient and capable of providing adequate solutions for even quite large instances). A simple local search procedure which incorporates problem specific information is also proposed.The computational results show that the proposed metaheuristics clearly outperform the best of the existing procedures. Also, they provide an optimal solution for all (or nearly all, in the case of the variable greedy heuristic) the smaller size problems. The metaheuristics are quite close in what regards solution quality. Nevertheless, the iterated local search method provides the best solution, though at the expense of additional computational time. The exact opposite is true for the variable greedy procedure, while the genetic algorithm is a good all-around performer.     

Key based data analytics across data centers considering bi-level resource provision in cloud computing

Due to the distribution characteristic of the data source, such as astronomy and sales, or the legal prohibition, it is not always practical to store the world-wide data in only one data center (DC). Hadoop is a commonly accepted framework for big data analytics. But it can only deal with data within one DC. The distribution of data necessitates the study of Hadoop across DCs. In this situation, though, we can place mappers in the local DCs, where to place reducers is a great challenge, since each reducer needs to process almost all map output across all involved DCs. In this paper, a novel architecture and a key based scheme are proposed which can respect the locality principle of traditional Hadoop as much as possible while realizing deployment of reducers with lower costs. Considering both the DC level and the server level resource provision, bi-level programming is used to formalize the problem and it is solved by a tailored two level group genetic algorithm (TLGGA). The final results, which may be dispersed in several DCs, can be aggregated to a designative DC or the DC with the minimum transfer and storage cost. Extensive simulations demonstrate the effectiveness of TLGGA. It can outperform both the baseline and the state-of-the-art mechanisms by 49% and 40%, respectively.     

Multivariable design of improved linear quadratic regulation control for MIMO industrial processes

In this study, a multivariable linear quadratic control system using a new state space structure was developed for the chamber pressure in the industrial coke furnace. Such processes typically have complex and nonlinear dynamic behavior, which causes the performance of controllers using conventional design and tuning to be poor or to require significant effort in practice. The process model is first treated into a new state space form and the implementation of linear quadratic control is designed using this new model structure. Performance in terms of regulatory/servo, disturbance rejection and measurement noise problems were all compared with the recent model predictive control strategy. Results revealed that the control system showed more robustness and improved the closed-loop process performance under model/process mismatches.