scholarly journals A new approach based on inventory control using interval differential equation with application to manufacturing system

2021 ◽  
Vol 0 (0) ◽  
pp. 0
Author(s):  
Md Sadikur Rahman ◽  
Subhajit Das ◽  
Amalesh Kumar Manna ◽  
Ali Akbar Shaikh ◽  
Asoke Kumar Bhunia ◽  
...  
Keyword(s):  
Differential Equations ◽  
Optimization Technique ◽  
Parametric Representation ◽  
Solution Procedure ◽  
Parametric Form ◽  
Manufacturing Firm ◽  
Proposed Model ◽  
Linear Interval ◽  
Arithmetic System ◽  
Mixing Problem

<p style='text-indent:20px;'>Now-a-days, uncertainty conditions play an important role in modelling of real-world problems. In this regard, the aim of this study is two folded. Firstly, the concept of system of interval differential equations and its solution procedure in the parametric approach have been proposed. To serve this purpose, using parametric representation of interval and its arithmetic, system of linear interval differential equations is converted to the system of differential equations in parametric form. Then, a mixing problem with three liquids is considered and the mixing process is governed by system of interval differential equations. Thereafter, the mixing liquid is used in the production process of a manufacturing firm. Secondly, using this concept, a production inventory model for single item has been developed by employing mixture of liquids and the proposed production system is formulated mathematically by using system of interval differential equations.The corresponding interval valued average profit of the proposed model has been obtained in parametric form and it is maximized by centre-radius optimization technique. Then to validate the proposed model, two numerical examples have been solved using MATHEMATICA software. In addition, we have shown the concavity of the objective function graphically using the code of 3D plot in MATHEMATICA. Finally, the post optimality analyses are carried out with respect to different system parameters.</p>

Business management in the football industry from a supply chain management perspective

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Zhaleh Memari ◽  
Abbas Rezaei Pandari ◽  
Mohammad Ehsani ◽  
Shokufeh Mahmudi
Keyword(s):  
Supply Chain ◽  
Supply Chain Management ◽  
Business Management ◽  
Relationship Management ◽  
Flow Management ◽  
Manufacturing Firm ◽  
Chain Management ◽  
Content Type ◽  
Proposed Model ◽  
Football Industry

PurposeTo understand the football industry in its entirety, a supply chain management (SCM) approach is necessary. This includes the study of suppliers, consumers and their collaborations. The purpose of this study was to present a business management model based on supply chain management.Design/methodology/approachData were collected through in-depth interviews with 12 academic and executive football experts. After three steps of open, axial and selective coding based on grounded theory with a paradigmatic approach, the data were analysed, and a football supply chain management (FSCM) was developed. The proposed model includes three managerial components: upstream suppliers, the manufacturing firm, and downstream customers.FindingsThe football industry sector has three parts: upstream suppliers, manufacturing firm/football clubs and downstream customers. We proposed seven parts for the managerial processes of football supply chain management: event/match management, club management, resource and infrastructure management, customer relationship management, supplier relationship management, cash flow management and knowledge and information flow management. This model can be used for configuration, coordination and redesign of business operations as well as the development of models for evaluation of the football supply chain's performance.Originality/valueThe proposed model of a football supply chain management, with the existing literature and theoretical review, created a synergistic outcome. This synergy is presented in the linkage of the players in this chain and interactions between them. This view can improve the management of industry productivity and improve the products quality.

Designing a sustainable supply chain network for producing high-value products from waste glass

2021 ◽  
pp. 0734242X2199466
Author(s):  
Naeme Zarrinpoor
Keyword(s):  
Supply Chain ◽  
Greenhouse Gas Emission ◽  
Fuzzy Programming ◽  
Solution Procedure ◽  
Waste Glass ◽  
Worker Safety ◽  
Programming Approach ◽  
Supply Chain Network ◽  
Sustainable Supply Chain ◽  
Proposed Model

This paper aims to design a supply chain network for producing double glazed glass from the recycling of waste glass. All three pillars of sustainability are taken into consideration. The economic objective tries to maximize total profits. The environmental objective considers the energy consumption, the generated waste, the greenhouse gas emission, the water consumption, and the fuel consumption of vehicles. The social objective addresses created job opportunities, the worker safety, the regional development, the worker benefit, and training hours. To solve the model, a two-stage framework based on the group best-worst method and an interactive fuzzy programming approach is developed. The proposed model is validated through a real case study based on waste glass management in the city of Shiraz. It is revealed that when sustainable development goals are approached, a great degree of improvement will be attained in environmental and social aspects without a significant decrease in the economic sustainability. The results also demonstrate that the locations of glass recycling centres are different under economic, environmental, and social pillars, and the proposed model yields an optimal system configuration with a proper satisfaction degree of all objectives. Moreover, applying the proposed solution procedure enables system designers to obtain the most desirable trade-off between different aspects of sustainability.

Analysis of a New Class of Impulsive Implicit Sequential Fractional Differential Equations

2020 ◽  
Vol 21 (6) ◽  
pp. 571-587 ◽  
Author(s):  
Akbar Zada ◽  
Sartaj Ali ◽  
Tongxing Li
Keyword(s):  
Differential Equations ◽  
Fractional Order ◽  
Fractional Differential Equations ◽  
Sufficient Conditions ◽  
Uniqueness Of Solutions ◽  
Integer Order ◽  
New Class ◽  
Proposed Model ◽  
Fractional Differential ◽  
Sequential Fractional Differential Equations

AbstractIn this paper, we study an implicit sequential fractional order differential equation with non-instantaneous impulses and multi-point boundary conditions. The article comprehensively elaborate four different types of Ulam’s stability in the lights of generalized Diaz Margolis’s fixed point theorem. Moreover, some sufficient conditions are constructed to observe the existence and uniqueness of solutions for the proposed model. The proposed model contains both the integer order and fractional order derivatives. Thus, the exponential function appearers in the solution of the proposed model which will lead researchers to study fractional differential equations with well known methods of integer order differential equations. In the last, few examples are provided to show the applicability of our main results.

Optimal Trajectories of Open-Chain Robot Systems: A New Solution Procedure Without Lagrange Multipliers

1998 ◽  
Vol 120 (1) ◽  
pp. 134-136 ◽  
Author(s):  
Sunil K. Agrawal ◽  
Pana Claewplodtook ◽  
Brian C. Fabien
Keyword(s):  
Differential Equations ◽  
Lagrange Multipliers ◽  
Nonlinear Differential Equations ◽  
Boundary Value ◽  
Optimal Solution ◽  
Solution Procedure ◽  
Optimal Trajectories ◽  
Point Boundary ◽  
Open Chain ◽  
Robot Systems

For an n d.o.f. robot system, optimal trajectories using Lagrange multipliers are characterized by 4n first-order nonlinear differential equations with 4n boundary conditions at the two end time. Numerical solution of such two-point boundary value problems with shooting techniques is hard since Lagrange multipliers can not be guessed. In this paper, a new procedure is proposed where the dynamic equations are embedded into the cost functional. It is shown that the optimal solution satisfies n fourth-order differential equations. Due to absence of Lagrange multipliers, the two-point boundary-value problem can be solved efficiently and accurately using classical weighted residual methods.

scholarly journals Optimization technique combined with deep learning method for teeth recognition in dental panoramic radiographs

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Fahad Parvez Mahdi ◽  
Kota Motoki ◽  
Syoji Kobashi
Keyword(s):  
Dental Care ◽  
Cross Validation ◽  
Optimization Technique ◽  
Confidence Score ◽  
Computer Assisted ◽  
Proposed Model ◽  
Tenfold Cross Validation ◽  
Stress Fatigue ◽  
Assisted Analysis ◽  
High Degree

Abstract Computer-assisted analysis of dental radiograph in dentistry is getting increasing attention from the researchers in recent years. This is mainly because it can successfully reduce human-made error due to stress, fatigue or lack of experience. Furthermore, it reduces diagnosis time and thus, improves overall efficiency and accuracy of dental care system. An automatic teeth recognition model is proposed here using residual network-based faster R-CNN technique. The detection result obtained from faster R-CNN is further refined by using a candidate optimization technique that evaluates both positional relationship and confidence score of the candidates. It achieves 0.974 and 0.981 mAPs for ResNet-50 and ResNet-101, respectively with faster R-CNN technique. The optimization technique further improves the results i.e. F1 score improves from 0.978 to 0.982 for ResNet-101. These results verify the proposed method’s ability to recognize teeth with high degree of accuracy. To test the feasibility and robustness of the model, a tenfold cross validation (CV) is presented in this paper. The result of tenfold CV effectively verifies the robustness of the model as the average F1 score obtained is more than 0.970. Thus, the proposed model can be used as a useful and reliable tool to assist dental care professionals in dentistry.

A 2D Numerical Model for Simulation of Two-Dimensional Circular Dam-Break

2011 ◽  
Vol 130-134 ◽  
pp. 2993-2996
Author(s):  
Ming Qin Liu ◽  
Y.L. Liu
Keyword(s):  
Solution Procedure ◽  
Dam Break ◽  
Curvilinear Coordinates ◽  
Two Dimensional ◽  
Proposed Model ◽  
Curvilinear Coordinate ◽  
Orthogonal Curvilinear Coordinate System ◽  
Orthogonal Curvilinear Coordinates ◽  
Averaged Model ◽  
The Mathematical Model

The purpose of this paper is to present a 2D depth-averaged model under orthogonal curvilinear coordinates for simulating two-dimensional circular dam-break flows. The proposed model uses an orthogonal curvilinear coordinate system efficiently and accurately to simulate the flow field with irregular boundaries. As for the numerical solution procedure, The SIMPLEC solution procedure has been used for the transformed governing equations in the transformed domain. Practical application of the model is illustrated by an example, which demonstrates that the mathematical model can capture hydraulic discontinuities accurately such as steep fronts, hydraulic jump and drop, etc.

scholarly journals A New Click-Through Rates Prediction Model Based on Deep&Cross Network

Algorithms ◽  
2020 ◽  
Vol 13 (12) ◽  
pp. 342
Author(s):  
Guojing Huang ◽  
Qingliang Chen ◽  
Congjian Deng
Keyword(s):  
Neural Networks ◽  
Prediction Model ◽  
Deep Neural Networks ◽  
Prediction Models ◽  
State Of The Art ◽  
Online Advertising ◽  
Optimization Technique ◽  
Proposed Model ◽  
Great Progress ◽  
Online Advertisement

With the development of E-commerce, online advertising began to thrive and has gradually developed into a new mode of business, of which Click-Through Rates (CTR) prediction is the essential driving technology. Given a user, commodities and scenarios, the CTR model can predict the user’s click probability of an online advertisement. Recently, great progress has been made with the introduction of Deep Neural Networks (DNN) into CTR. In order to further advance the DNN-based CTR prediction models, this paper introduces a new model of FO-FTRL-DCN, based on the prestigious model of Deep&Cross Network (DCN) augmented with the latest optimization technique of Follow The Regularized Leader (FTRL) for DNN. The extensive comparative experiments on the iPinYou datasets show that the proposed model has outperformed other state-of-the-art baselines, with better generalization across different datasets in the benchmark.

scholarly journals Computational Optimization of Residual Power Series Algorithm for Certain Classes of Fuzzy Fractional Differential Equations

2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Mohammad Alaroud ◽  
Mohammed Al-Smadi ◽  
Rokiah Rozita Ahmad ◽  
Ummul Khair Salma Din
Keyword(s):  
Power Series ◽  
Differential Equations ◽  
Fractional Differential Equations ◽  
Optimization Technique ◽  
Fractional Power ◽  
Taylor Formula ◽  
Residual Power Series ◽  
Fractional Differential ◽  
Residual Power ◽  
Fuzzy Fractional Differential Equations

This paper aims to present a novel optimization technique, the residual power series (RPS), for handling certain classes of fuzzy fractional differential equations of order 1<γ≤2 under strongly generalized differentiability. The proposed technique relies on generalized Taylor formula under Caputo sense aiming at extracting a supportive analytical solution in convergent series form. The RPS algorithm is significant and straightforward tool for creating a fractional power series solution without linearization, limitation on the problem’s nature, sort of classification, or perturbation. Some illustrative examples are provided to demonstrate the feasibility of the RPS scheme. The results obtained show that the scheme is simple and reliable and there is good agreement with exact solution.

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