A Note on One-Dimensional Cutting Stock Problem

In the cutting stock problem (CSP) a given order for smaller pieces has to be cut from larger stock material with some objectives under some constraints. This note discusses the relationships between the models for one-dimensional cutting stock problem (1CSP) under two different constraints and two different objectives. The two constraints are equality and inequality constraints; and the two objectives are to minimize the number and the trim loss of stock material needed to produce the ordered pieces. Under equality constraint, we have proved that the models with both objectives are equivalent, and their corresponding continuous relaxation problems are also equivalent. Under inequality constraint, we have given an example to show that the models with these two objectives are not equivalent, and their corresponding continuous relaxation problems are also not equivalen

Monitoring of Tsunami/Earthquake Damages by Polarimetric Microwave Remote Sensing Technique

Polarization characterizes the vector state of EM wave. When interacting with polarized wave, rough natural surface often induces dominant surface scattering; building also presents dominant double-bounce scattering. Tsunami/earthquake causes serious destruction just by inundating the land surface and destroying the building. By analyzing the change of surface and double-bounce scattering before and after disaster, we can achieve a monitoring of damages. This constitutes one basic principle of polarimetric microwave remote sensing of tsunami/earthquake. The extraction of surface and double-bounce scattering from coherency matrix is achieved by model-based decomposition. The general four-component scattering power decomposition with unitary transformation (G4U) has been widely used in the remote sensing of tsunami/earthquake to identify surface and double-bounce scattering because it can adaptively enhance surface or double-bounce scattering. Nonetheless, the strict derivation in this chapter conveys that G4U cannot always strengthen the double-bounce scattering in urban area nor strengthen the surface scattering in water or land area unless we adaptively combine G4U and its duality for an extended G4U (EG4U). Experiment on the ALOS-PALSAR datasets of 2011 great Tohoku tsunami/earthquake demonstrates not only the outperformance of EG4U but also the effectiveness of polarimetric remote sensing in the qualitative monitoring and quantitative evaluation of tsunami/earthquake damages

Magnetostrictive and magnetoelectric behavior of Fe–20 at. % Ga/Pb(Zr,Ti)O3 laminates

The magnetostrictive and magnetoelectric (ME) properties of laminate composites of Fe–20 at. % Ga and Pb(Zr,Ti)O3 (PZT) have been studied for laminates of different geometries. The results show that (i) a long-type magnetostrictive Fe–20 at. % Ga crystal plate oriented along 〈001〉c and magnetized in its longitudinal (or length) direction has higher magnetostriction than a disk-type one; and consequently (ii) a long-type Fe–20 at. % Ga/PZT laminate has a giant ME effect, and is sensitive to low-level magnetic fields

Fe–Ga/Pb(Mg1/3Nb2/3)O3–PbTiO3 magnetoelectric laminate composites

We have found large magnetoelectric (ME) effects in long-type laminate composites of Fe–20%Ga magnetostrictive alloys and piezoelectric Pb(Mg1/3Nb2/3)O3–PbTiO3 single crystals. At lower frequencies, the ME voltage coefficient of a laminate with longitudinally magnetized and longitudinally polarized (i.e., L-L mode) layers was 1.41 V/Oe (or1.01 V/cm Oe). Near the natural resonant frequency ( ∼ 91 kHz) of the laminate, the ME voltage coefficients were found to be dramatically increased to 50.7 V/Oe (36.2 V/cm Oe)for the L-L mode. In addition, the laminate can detect a minute magnetic field as low as ∼ 2×10−12 T at resonance frequency, and ∼ 1×10−10 T at lower frequencies

Heuristic genetic algorithms for general capacitated lot-sizing problems

AbstractThe lot-sizing problems address the issue of determining the production lot-sizes of various items appearing in consecutive production stages over a given finite planning horizon. In general capacitated lot-sizing problems, the product structure can be a general acyclic network, the capacity constraints can be very sophisticated, and all the known parameters can be time-varying. This paper proposes heuristic genetic algorithms for these problems by designing a domain-specific encoding scheme for the lot-sizes and by providing a heuristic shifting procedure as the decoding schedule. The main contribution of these genetic algorithms is the presentation technique that encodes only the binary variables for the setup patterns but derives other decision variables by making use of the problem-specific knowledge. Some results from the computational experiments are also given

Multi-Objective Optimization of Microstructure of Gravure Cell Based on Response Surface Method

In order to improve the structural stiffness of the gravure cell structure in the solid printing process and realize a lightweight design, a multi-objective optimization design method was proposed to optimize the parameters of the direct laser engraving of the cell structure. In this paper, based on the characteristics of the cell structure and the analysis of the contact force, the ANSYS parametric design language (APDL) was used to conduct a finite element analysis on the microstructure of the regular hexagonal cell. We found that there is a certain optimization space. Then, a response surface (RSM) method optimization model, using a central composite design (CCD), was established to obtain, and then analyze, the sensitivity of each design variable to the objective functions. Finally, a multi-objective genetic algorithm (MOGA) was used to solve the model. The optimization results show that the maximum deformation was reduced by 44.4%, and the total volume was reduced by 46.3%. By comparing with the model before optimization, the rationality and effectiveness of this method were verified. This shows that the method can be effectively applied to the design optimization of gravure cell microstructure, and it provides theoretical support for new cell design

Moving Low-Carbon Transportation in Xinjiang: Evidence from STIRPAT and Rigid Regression Models

With the rapid economic development of the Xinjiang Uygur Autonomous Region, the area’s transport sector has witnessed significant growth, which in turn has led to a large increase in carbon dioxide emissions. As such, calculating of the carbon footprint of Xinjiang’s transportation sector and probing the driving factors of carbon dioxide emissions are of great significance to the region’s energy conservation and environmental protection. This paper provides an account of the growth in the carbon emissions of Xinjiang’s transportation sector during the period from 1989 to 2012. We also analyze the transportation sector’s trends and historical evolution. Combined with the STIRPAT (Stochastic Impacts by Regression on Population, Affluence and Technology) model and ridge regression, this study further quantitatively analyzes the factors that influence the carbon emissions of Xinjiang’s transportation sector. The results indicate the following: (1) the total carbon emissions and per capita carbon emissions of Xinjiang’s transportation sector both continued to rise rapidly during this period; their average annual growth rates were 10.8% and 9.1%, respectively; (2) the carbon emissions of the transportation sector come mainly from the consumption of diesel and gasoline, which accounted for an average of 36.2% and 2.6% of carbon emissions, respectively; in addition, the overall carbon emission intensity of the transportation sector showed an “S”-pattern trend within the study period; (3) population density plays a dominant role in increasing carbon dioxide emissions. Population is then followed by per capita GDP and, finally, energy intensity. Cargo turnover has a more significant potential impact on and role in emission reduction than do private vehicles. This is because road freight is the primary form of transportation used across Xinjiang, and this form of transportation has low energy efficiency. These findings have important implications for future efforts to reduce the growth of transportation-based carbon dioxide emissions in Xinjiang and for any effort to construct low-carbon and sustainable environments

Spatiotemporal Features and Socioeconomic Drivers of PM_2.5 Concentrations in China

Fine particulate matter (PM2.5) has been an important environmental issue because it can seriously harm human health and can adversely affect the economy. It poses a problem worldwide and especially in China. Based on data of PM2.5 concentration and night light data, both collected from satellite remote sensing during 1998⁻2013 in China, we identify the socio-economic determinants of PM2.5 pollution by taking into account the spatial flow and diffusion of regional pollutants. Our results show PM2.5 pollution displays the remarkable feature of spatial agglomeration. High concentrations of PM2.5 are mainly found in Eastern China (including Shandong, Jiangsu, and Anhui provinces) and the Jing-Jin-Ji Area region in the north of China (including Beijing, Tianjin, and Hebei provinces) as well as in the Henan provinces in central China. There is a significant positive spatial spillover effect of PM2.5 pollution, so that an increase in PM2.5 concentration in one region contributes to an increase in neighboring regions. Whether using per capita GDP or nighttime lighting indicators, there is a significant N-shaped curve that relates PM2.5 concentration and economic growth. Population density, industrial structure, and energy consumption have distinct impacts on PM2.5 pollution, while urbanization is negative correlated with PM2.5 emissions. As a result, policies to strengthen regional joint prevention and control, implement cleaner manufacturing techniques, and reduce dependence on fossil fuels should be considered by policy makers for mitigating PM2.5 pollution

Regional Inequality in China Based on NPP-VIIRS Night-Time Light Imagery

Regional economic inequality is a persistent problem for all nations. Meanwhile, satellite-derived night-time light (NTL) data have been extensively used as an efficient proxy measure for economic activity. This study firstly proposes a new method for correction of the NTL data derived from the Visible Infrared Imaging Radiometer Suite (VIIRS) aboard the Suomi National Polar-orbiting Partnership (Suomi-NPP) satellite and then applies the corrected NTL data to estimate gross domestic product (GDP) at a multi-scale level in China from 2014 to 2017. Secondly, incorporating the two-stage nested Theil decomposition method, multi-scale level regional inequalities are investigated. Finally, by using scatter plots, this paper identifies the relationship between the regional inequality and the level of economic development. The results indicate that: (1) after correction, the NPP-VIIRS NTL data show a statistically positive correlation with GDP, which proves that our correction method is scientifically effective; (2) from 2014 to 2017, overall inequality, within-province inequality, and between-region inequality all declined, However, between-province inequality increased slightly. As for the contributions to overall regional inequality, the within-province inequality was the highest, while the between-province inequality was the lowest; (3) further analysis of within-province inequality reveals that economic inequalities in coastal provinces in China are smaller than in inland provinces; (4) China’s economic development plays an important role in affecting regional inequality, and the extent of influence of economic development on regional inequality is varied across provinces