Proton exchange membrane fuel cells (PEMFCs) are among the promising alternatives for clean energy generation, especially when hydrogen is the fuel used. Their operation is still faced with several challenges, and one...
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We investigated the optimum hand-picking time of Nagano Purple, a rare Japanese table grape variety. The color sensitivity between pure red–purple–black and pure purple–black makes it difficult for farmers to harve...
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The purpose of this article is to introduce and test a model for green performance assessment in supply chains. The research method was the qualitative modeling. By literature review a model was proposed, consisting o...
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The purpose of this article is to introduce and test a model for green performance assessment in supply chains. The research method was the qualitative modeling. By literature review a model was proposed, consisting of three constructs described and appraised by categorical indicators: green strategy;green innovation;and green operations. The model originated a scale, with five degrees for the measurement of the indicators: very good=1;good=0.75;neutral=0.5;bad=0.25;very bad=0. An application was made in a supply chain of the footwear industry. Focal company managers were asked to distribute importance among the constructs and fulfill the scale. Outcomes obtained, with uniform distribution, and weighted by AHP methods, reached close to 40% of the maximum possible. The worst-performing construct and indicators were operations, reverse logistics and green distribution. Actions have been proposed to improve them.
This article presents a model for performance measurement in supply chains. The methodology had two-steps: a qualitative part to identify constructs and indicators and a quantitative one to measure them. The model has...
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This article presents a model for performance measurement in supply chains. The methodology had two-steps: a qualitative part to identify constructs and indicators and a quantitative one to measure them. The model has two dimensions: SCOR model process: source, make, deliver, and return;and priorities: cost, quality, delivery, flexibility. A 4 x 4 matrix resulted, weighted by AHP. In the cells, indicators, with ranges and five categories [very good, good, neutral, bad, very bad] were allocated to appraise the priority in the process. The ranges were set in the planning process of SCOR. An application was done in the hard core of a supply chain of the footwear industry, including 72 indicators in four suppliers;the focal company;three distribution channels;and a return channel. The SC overall performance reached near 80% of the maximum possible value. Worst performance was flexibility in deliver and delivery in make.
The aim of this paper is to compare and discuss better classifier algorithm options for credit risk assessment by applying different Machine Learning techniques. Using records from a Brazilian financial institution, t...
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The strong competitiveness challenges manufacturing industry to rationalize different ways of bringing new products to the market in the shortest time with competitive prices while ensuring higher quality. Industries ...
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To improve production processes, manufacturing companies have made efforts to implement Industry 4.0 technologies and spread the use of Lean Manufacturing (LM) tools. Besides, in addition to the improvements in produc...
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In a world where the information is obtained faster than ever seem, new methods to process that high volume of data are being developed frequently. This is more notorious in a virtual ambient where the data is generat...
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Traveling Salesman Problem (TSP) is one of the most difficult problems in the Combinatorial Optimization area. The goal of TSP is to find one path that can travel between all the nodes (instances) of the graph just on...
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ISBN:
(纸本)9781424429141
Traveling Salesman Problem (TSP) is one of the most difficult problems in the Combinatorial Optimization area. The goal of TSP is to find one path that can travel between all the nodes (instances) of the graph just once (Hamiltonian tour) in the smallest tour, that is, smallest Euclidian distance. In this context, many other meta-heuristics techniques based on evolutionary algorithms have been propose in literature to solve TSP problems. Differential Evolution (DE) is a relatively new simple evolutionary algorithm, which is an effective adaptive approach to global optimization over continuous search spaces. The design principles of DE are simplicity and efficiency. The most distinct feature of DE is that it mutates vectors by adding weighted. random vector differentials to them. Since its invention. DE has been applied with high success on many numerical optimization problems outperforming other more popular meta-heuristics such as the genetic algorithms. Recently. some researchers extended with success the application of DE to complex combinatorial optimization problems with discrete decision variables such as the traveling salesman problem, the machine layout problem, the now-shop scheduling problem. In this paper, the following discrete DE approaches for the TSP are proposed and evaluated: i) DE approach without local search, ii) DE with local search based on Lin-Kernighan-Heulsgaun (LKH) method, and iii) DE with local search based on Variable Neighborhood Search (VNS) and together with LKH method. Numerical study is carried out using the TSPLIB of test TSP problems. In this context, the computational results are compared with the other results in the recent TSP literature. The obtained results show that LKH method is the best method to reach optimal results for TSPLIB benchmarks, but for largest problems, the ED+VNS improve the quality of obtained results.
This study comprehensively describes the application of linear electromagnetic actuators in automotive suspension systems, focusing on the electromagnetic force necessary in suspension systems operating in passive, se...
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