A genetic algorithm for the single machine preemptive scheduling problem with linear earliness and quadratic tardiness penalties

In this paper, we consider the single machine preemptive scheduling problem with linear earliness and quadratic tardiness penalties, with no machine idle time. The problem is strongly NP-hard. We proposed a new mathematical model, with non-linear terms and integer variables. We develop a genetic algorithm for solving the problem in medium and large size. The proposed procedure is compared with optimal solutions for the smaller instance sizes. The genetic procedure is also quite close to the optimum and provided an optimal solution for most of the test problems. Numerical examples show that the proposed algorithm is efficient and effective. Scheduling with early and tardy penalties has received extensive attention from the scheduling community because of its practical significance. Single machine scheduling environments actually occur in several practical applications. Also, the performance of many production systems is often determined by the schedules for a single bottleneck machine. Furthermore, the study of single machine problems frequently provides outcomes that prove functional for more complex scheduling areas.     

Experimental analysis and prediction of viscoelastic creep properties of PP/EVA/LDH nanocomposites using master curves based on time–temperature superposition

Prediction of viscoelastic behavior of polymers over a long‐term period is of vital importance for engineering applications. An attempt was made to uncover the interplay between the morphology and viscoelastic behavior of compatibilized polypropylene/ethylene vinyl acetate (EVA) copolymer blends in the presence of layered double hydroxide (LDH) nanoplatelets. The time–temperature superposition (TTS) principle and WLF equations were merged to obtain master curves of storage modulus at defined reference temperatures enabling prediction of storage modulus at high frequency ranges which are not experimentally measureable. Moreover, the creep compliance master curves were acquired for different reference temperatures to predict the creep compliance of nanocomposites over long period of times. It was found that the presence of LDH decreases the creep compliance at long period of times while it decreases the unrecoverable deformation of EVA domains. A simple mechanism was proposed to explain the creep and recovery behavior of samples blend at different temperatures. © 2018 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2018 , 135, 46725.     

A reliable and efficient micro-protocol for data transmission over an RTP-based covert channel

Multimedia Systems - As the VoIP steganographic methods provide a low capacity covert channel for data transmission, an efficient and real-time data transmission protocol over this channel is...     

Homogeneous polymerization of ethylene using an iron‐based metal catalyst system

An iron‐based catalyst of 2,6‐bis‐[1‐(2‐methylphenylimino)ethyl]pyridine iron dichloride was prepared. The ligand was prepared using 2,6‐diacetylpyridine as the starting chemical under controlled conditions. The preparation procedure was followed using ¹³C‐NMR, ¹H‐NMR, FT‐IR, MS (mass spectroscopy), and elemental analysis methods. The homogeneous polymerization of ethylene was carried out using the prepared catalyst in toluene media. Methyl aluminoxane (MAO) was used as a cocatalyst. The effect of the [Al] : [Fe] molar ratio, polymerization temperature, and monomer pressure of 202,000 to 454,500 Pa on the polymerization behavior were studied. The highest activity of the catalyst was obtained at 30°C, the activity decreased with increasing temperature, while increasing pressure linearly increased its activity. The molecular weight distribution of the polyethylene obtained was 1.25 to 1.72. A weight average molecular weight of 7.1 × 10⁴ and 1.5 × 10³ were obtained. The crystallinity of the polymer was about 19% and its melting point was about 65°C. © 2006 Wiley Periodicals, Inc. J Appl Polym Sci 103: 1517–1522, 2007     

Response of Triangular-Shaped Leaky Aquifers to Rainfall-Induced Groundwater Recharge: an Analytical Study

Different aspects of groundwater mound dynamics in triangular-shaped aquifers are investigated analytically under spatially uniform recharge of time-varying rate. The aquifer response is analyzed relying on 2-D linearized Boussinesq equation, subject to two different configurations of hydrogeological boundary conditions (constant-head streams and no-flow barrier). The aquifer is homogeneous, isotropic and rests over a horizontal, semipervious layer, through which vertical leakage can take place. Point-recharge formula (Green’s function) is first derived for the intended aquifer domain and then properly converted to accommodate the effect of rainfall-induced areal recharge. Components of groundwater budget are evaluated in terms of volumetric rates, taking into account the jointed effects of leakage, mound storage and outflow to adjacent streams. The resulting expressions are then proven to obey the expected mass balance in a rigorous mathematical fashion. Hypothetical examples illustrating main features of flow field are presented, with attention paid on groundwater equpotentials and streamlines. The computed mound profiles appear to agree well with numerical results from finite element method. Further, the most influential parameters affecting each component of groundwater budget are identified with the help of sensitivity analysis. Finally, the combined effects of a pumping well and rainfall-induced mound are discussed. The present solution may serve as a test case for verifying numerical schemes that are being developed for more comprehensive mound analysis.

     

A simple model for the derivation of illuminance values from global solar radiation data

This paper presents a new simple luminous efficacy model for global horizontal irradiance. The objective is to derive values of outdoor global horizontal illuminance data from typical local weather station data including global horizontal irradiance and Humidity Ratio of outdoor air. The proposed luminous efficacy model incorporates, as the main influencing variable, the Clearness Factor, which is an original derivative from the Clearness Index. Two further variables are included in the model formulation. These are the Humidity Ratio and the solar altitude. Moreover, the model includes a location-dependent variable, which may be derived from the latitude information. The paper includes the result of the statistical analysis of the relationship between the model predictions and the measured data. The results of this analysis display a good agreement between predictions and measurements.     

Application of neural networks and State-space averaging to DC/DC PWM converters in sliding-mode operation

A novel output feedback neural controller is presented in This work for the implementation of sliding-mode control of dc/dc converters. The controller, which consists of a multilayer perceptron, has been trained in order to be robust for large variations of system parameters and state variables. Fast dynamic behavior is the other main advantage of the proposed controller, which allows realization of all beneficial features of the sliding-mode control technique. Other advantages of the controller are simplicity and low cost. Computer simulations have been carried out to investigate the effectiveness of the controller in voltage regulation for a relatively complex dc/dc converter topology of the Cuk converter. Simulation results confirm the excellent performance of the control system in response to large signal variations. In order to verify the simulation results, a controller prototype has been designed and built using analog components. The controller is applied to regulate the output voltage of the Cuk converter. Experimental results confirm the analytical and simulation achievements.     

A genetic algorithm for optimization problems with fuzzy relation constraints using max-product composition

We consider nonlinear optimization problems constrained by a system of fuzzy relation equations. The solution set of the fuzzy relation equations being nonconvex, in general, conventional nonlinear programming methods are not practical. Here, we propose a genetic algorithm with max-product composition to obtain a near optimal solution for convex or nonconvex solution set. Test problems are constructed to evaluate the performance of the proposed algorithm showing alternative solutions obtained by our proposed model.