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Publisher: Redfame Publishing (Total: 7 journals) [Sort by number of followers]

Showing 1 - 7 of 7 Journals sorted alphabetically
	Applied Economics and Finance (Followers: 9)
	Applied Finance and Accounting (Followers: 8)
	Business and Management Studies (Followers: 12)
	Intl. J. of Social Science Studies (Followers: 13)
	J. of Education and Training Studies (Followers: 4)
	Studies in Engineering and Technology
	Studies in Media and Communication (Followers: 15, SJR: 0.401, CiteScore: 1)

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Studies in Engineering and Technology
Number of Followers: 0

This is an Open Access Journal

Open Access journal
ISSN (Print) 2330-2038 - ISSN (Online) 2330-2046
Published by Redfame Publishing

[7 journals]

An Optimization Model for Ordering and Transporting Raw Materials by
Manufacturers Based on Linear Programming
- Authors: Chengjia Huang; Zhengyong Chen, Sitong Chen
  Abstract: This study applies analytic hierarchy process (AHP), 0-1 integer programming and other systematic programming models, combined with the needs of manufacturers to build a set of mathematical models to help manufacturers select suppliers, control raw material ordering costs, and transporting costs. As the production costs of products is linked to the ordering and transporting of raw materials, manufacturers need to choose suitable raw material suppliers and develop the most economical ordering and transporting schemes with the most negligible loss so as to improve profits and enhance the market competitiveness. Taking a building and decorative plate enterprise as a case, this model shows that AHP can effectively quantify the supplying characteristics of suppliers and obtain a list of high-quality suppliers. LINGO software combined with linear programming can be used to obtain the optimal weekly ordering and transporting schemes, thus reducing the raw material ordering costs and transporting losses. It is shown from the results that the production costs of enterprises from the source can be reduced so as to improve their cost control system. The present study seeks to fill the gap in ordering and transporting raw materials for manufacturers to control production costs. At the same time, this model provides references for producers who have the demand for processing raw materials and play a significant role in controlling production costs.
  PubDate: Wed, 17 Aug 2022 00:00:00 -070
Bayesian Low-Rank Interpolative Decomposition for Complex Datasets
- Authors: Jun Lu
  Abstract: In this paper, we introduce a probabilistic model for learning interpolative decomposition (ID), which is commonly used for feature selection, low-rank approximation, and identifying hidden patterns in data, where the matrix factors are latent variables associated with each data dimension. Prior densities with support on the specified subspace are used to address the constraint for the magnitude of the factored component of the observed matrix. Bayesian inference procedure based on Gibbs sampling is employed. We evaluate the model on a variety of real-world datasets including CCLE EC50, CCLE IC50, CTRP EC50, and MovieLens 100K datasets with different sizes, and dimensions, and show that the proposed Bayesian ID GBT and GBTN models lead to smaller reconstructive errors compared to existing randomized approaches.
  PubDate: Thu, 30 Jun 2022 00:00:00 -070