Improved Layout Structure with Complexity Measures for the Manufacturer’s Pallet Loading Problem (MPLP) Using a Block Approach

Purpose: The purpose of this paper is to study the Manufacturers pallet-loading problem (MPLP), by loading identical small boxes onto a rectangle pallet to maximise the pallet utilization percentage while reducing the Complexity of loading. Design/methodology/approach: In this research a Block approach is proposed using a Mixed integer linear programming (MILP) model that generates layouts of an improved structure, which is very effective due to its properties in grouping boxes in a certain orientation along the X and Y axis. Also, a novel complexity index is introduced to compare the complexity for different pallet loading, which have the same pallet size but different box arrangements. Findings: The proposed algorithm has been tested against available data-sets in literature and the complexity measure and graphical layout results clearly demonstrate the superiority of the proposed approach compared with literature Manufacturers pallet-loading problem layouts. Originality/value: This study aids real life manufactures operations when less complex operations are essential to reduce the complexity of pallet loading

Retinoic acids increase expression of GLUT4 in dedifferentiated and hypertrophied cardiac myocytes

Sufficient expression of the insulin-sensitive glucose transporter GLUT4 may be crucial for the survival of cardiac myocytes in situations of stress. Expression of GLUT4 in cardiac myocytes correlates with cell differentiation and is reduced in the hypertrophied and failing myocardium. Adult rat cardiomyocytes (ARC) in primary culture undergo dedifferentiation and reduction of GLUT4 expression. Depending on the culture condition partial redifferentiation and/or hypertrophy follows. All-trans (at) and 9-cis retinoic acids (RA) are morphogenetic agents important for cell differentiation. Both atRA and 9-cisRA restored GLUT4 expression in dedifferentiated ARC, while only 9-cisRA could increase GLUT4 expression in hypertrophic ARC. The effects of RA were associated with improved differentiation of the cardiac myocytes, as assessed from the expression of atrial natriuretic factor and the morphology of the contractile apparatus. In neonatal rat cardiomyocytes, 9-cisRA, but not atRA, stimulated transcription from the glut4 promoter. In conclusion, treatment with RA can restore the down-regulated expression of GLUT4 in cardiomyocytes in association with a partial improvement of the differentiated phenotyp

Yang-Baxter maps and symmetries of integrable equations on quad-graphs

A connection between the Yang-Baxter relation for maps and the multi-dimensional consistency property of integrable equations on quad-graphs is investigated. The approach is based on the symmetry analysis of the corresponding equations. It is shown that the Yang-Baxter variables can be chosen as invariants of the multi-parameter symmetry groups of the equations. We use the classification results by Adler, Bobenko and Suris to demonstrate this method. Some new examples of Yang-Baxter maps are derived in this way from multi-field integrable equations.Comment: 20 pages, 5 figure

Mathematical programming for piecewise linear regression analysis

In data mining, regression analysis is a computational tool that predicts continuous output variables from a number of independent input variables, by approximating their complex inner relationship. A large number of methods have been successfully proposed, based on various methodologies, including linear regression, support vector regression, neural network, piece-wise regression, etc. In terms of piece-wise regression, the existing methods in literature are usually restricted to problems of very small scale, due to their inherent non-linear nature. In this work, a more efficient piece-wise linear regression method is introduced based on a novel integer linear programming formulation. The proposed method partitions one input variable into multiple mutually exclusive segments, and fits one multivariate linear regression function per segment to minimise the total absolute error. Assuming both the single partition feature and the number of regions are known, the mixed integer linear model is proposed to simultaneously determine the locations of multiple break-points and regression coefficients for each segment. Furthermore, an efficient heuristic procedure is presented to identify the key partition feature and final number of break-points. 7 real world problems covering several application domains have been used to demonstrate the efficiency of our proposed method. It is shown that our proposed piece-wise regression method can be solved to global optimality for datasets of thousands samples, which also consistently achieves higher prediction accuracy than a number of state-of-the-art regression methods. Another advantage of the proposed method is that the learned model can be conveniently expressed as a small number of if-then rules that are easily interpretable. Overall, this work proposes an efficient rule-based multivariate regression method based on piece-wise functions and achieves better prediction performance than state-of-the-arts approaches. This novel method can benefit expert systems in various applications by automatically acquiring knowledge from databases to improve the quality of knowledge base

Anisotropic swelling of elastomers filled with aligned 2D materials

A comprehensive study has been undertaken on the dimensional swelling of graphene-reinforced elastomers in liquids. Anisotropic swelling was observed for samples reinforced with graphene nanoplatelets (GNPs), induced by the in-plane orientation of the GNPs. Upon the addition of the GNPs, the diameter swelling ratio of the nanocomposites was significantly reduced, whereas the thickness swelling ratio increased and was even greater than that of the unfilled elastomers. The swelling phenomenon has been analyzed in terms of a modification of the Flory-Rhener theory. The newly-derived equations proposed herein, can accurately predict the dependence of dimensional swelling (diameter and thickness) on volume swelling, independent of the type of elastomer and solvent. The anisotropic swelling of the samples was also studied in combination with the evaluation of the tensile properties of the filled elastomers. A novel theory that enables the assessment of volume swelling for GNP-reinforced elastomers, based on the filler geometry and volume fraction has been developed. It was found that the swelling of rubber nanocomposites induces a biaxial constraint from the graphene flakes

An integrated platform for intuitive mathematical programming modeling using LaTeX

This paper presents a novel prototype platform that uses the same LaTeX mark-up language, commonly used to typeset mathematical content, as an input language for modeling optimization problems of various classes. The platform converts the LaTeX model into a formal Algebraic Modeling Language (AML) representation based on Pyomo through a parsing engine written in Python and solves by either via NEOS server or locally installed solvers, using a friendly Graphical User Interface (GUI). The distinct advantages of our approach can be summarized in (i) simplification and speed-up of the model design and development process (ii) non-commercial character (iii) cross-platform support (iv) easier typo and logic error detection in the description of the models and (v) minimization of working knowledge of programming and AMLs to perform mathematical programming modeling. Overall, this is a presentation of a complete workable scheme on using LaTeX for mathematical programming modeling which assists in furthering our ability to reproduce and replicate scientific work

Impact of NOx vehicle emission standards failure on Air Quality in Europe

Vehicle exhaust emission standards have been tightened in the EU for several decades now, in order to protect health and the environment. This has led to a substantial decrease in total pollutant emissions, despite the growing volumes of passenger and freight transport. However, national emissions, particularly of NOx, exceed the ceilings accorded under the Gothenburg Protocol of the UNECE's Convention on Long-Range Transboundary Air Pollution (LRTAP) (EEA 2012) in twelve EU Member States. The main reasons for such exceedances are that more diesel cars have been sold than originally predicted when fixing the targets, and that diesel cars emit much more than expected under real-world driving conditions. The latter appears as a consequence of the effort to achieve high fuel efficiency. While this has largely helped to control CO2 emissions, it was to the detriment of NOx. In this study we estimate what the impact of the different vehicle emission standards has been so far and to predict what the impact of upcoming emission standards will be in the future, using the best current knowledge on road transport activity statistics and emission factors in Europe. We present several sensitivity calculations to reflect the considerable uncertainty about the real-driving NOx emissions of diesel light duty vehicles. The results of this work can be useful in designing both limits for upcoming standards but also in assessing the impact of deviating from such limits. This is necessary in both deciding on the next steps of emission control policy and to relevant air quality prediction models

Stable optimisation-based scenario generation via game theoretic approach

Systematic scenario generation (SG) methods have emerged as an invaluable tool to handle uncertainty towards the efficient solution of stochastic programming (SP) problems. The quality of SG methods depends on their consistency to generate scenario sets which guarantee stability on solving SPs and lead to stochastic solutions of good quality. In this context, we delve into the optimisation-based Distribution and Moment Matching Problem (DMP) for scenario generation and propose a game-theoretic approach which is formulated as a Mixed-Integer Linear Programming (MILP) model. Nash bargaining approach is employed and the terms of the objective function regarding the statistical matching of the DMP are considered as players. Results from a capacity planning case study highlight the quality of the stochastic solutions obtained using MILP DMP models for scenario generation. Furthermore, the proposed game-theoretic extension of DMP enhances in-sample and out-of-sample stability with respect to the challenging problem of user-defined parameters variability