Using Mathematical Optimization Model to Discuss Different Dividends Tax Rate and Financing Capacity

2013 ◽  
Vol 12 (14) ◽  
pp. 2868-2872
Author(s):  
Yi Wu ◽  
Cunzhi Tian
Keyword(s):  
Optimization Model ◽  
Mathematical Optimization ◽  
Tax Rate ◽  
Mathematical Optimization Model

scholarly journals A Mathematical Optimization Model for Locating Telecenters

2012 ◽  
Vol 03 (03) ◽  
pp. 251-263 ◽  
Author(s):  
Morteza Tabatabaie Shourijeh ◽  
Mohammad Kermanshah ◽  
Amir Reza Mamdoohi ◽  
Ardeshir Faghri ◽  
Khaled Hamad
Keyword(s):  
Optimization Model ◽  
Mathematical Optimization ◽  
Mathematical Optimization Model

scholarly journals Optimal Semi-Competitive Intermediation Networks

2020 ◽  
Vol 20 (5) ◽  
pp. 81-94
Author(s):  
Amelia Bădică ◽  
Costin Bădică ◽  
Maria Ganzha ◽  
Mirjana Ivanović ◽  
Marcin Paprzycki
Keyword(s):  
Optimization Model ◽  
Numerical Optimization ◽  
Autonomous Agents ◽  
Mathematical Optimization ◽  
Optimal Strategies ◽  
Directed Acyclic Graphs ◽  
Pricing Strategies ◽  
Computational Results ◽  
Acyclic Graphs ◽  
Mathematical Optimization Model

AbstractIn this work we address the problem of optimizing collective profitability in semi-competitive intermediation networks defined as augmented directed acyclic graphs. Network participants are modeled as autonomous agents endowed with private utility functions. We introduce a mathematical optimization model for defining pricing strategies of network participants. We employ welfare economics aiming to maximize the Nash social welfare of the intermediation network. The paper contains mathematical results that theoretically prove the existence of such optimal strategies. We also discuss computational results that we obtained using a nonlinear convex numerical optimization package.

scholarly journals Dispatching continuous moves

2005 ◽  
Vol 16 (2) ◽  
pp. 25-37
Author(s):  
David Ronen
Keyword(s):  
Optimization Model ◽  
Mathematical Optimization ◽  
Trucking Industry ◽  
Mathematical Optimization Model

Continuous Moves (CM) is a term coined by the trucking industry. This paper defines CM’s, classifies them and discusses their economies. A unifying mathematical optimization model for dispatching orders is then presented. The model selects the best way to dispatch each and every order, whether as a part of a CM or not. However, the model does consider all the feasible types of CM’s. Practical aspects associated with implementing CM’s are also discussed.

Optimization Method Based on Genetic Evolution for Multiple-Stage Coordinate Mining of Multiple Mining Areas with same Coal

2013 ◽  
Vol 807-809 ◽  
pp. 2460-2469
Author(s):  
Qiang Zeng ◽  
Ze Bin Zhang ◽  
Zu Qiang Xiong ◽  
De Quo Xiong
Keyword(s):  
Optimization Model ◽  
Mathematical Optimization ◽  
Optimization Method ◽  
Great Difficulty ◽  
Simplified Model ◽  
Genetic Evolution ◽  
Total Sale ◽  
Mining Areas ◽  
Mathematical Optimization Model

Aiming at the multiple-stage coordinate mining problem for multiple mining areas with same coal, an optimization method based on genetic evolution is proposed. Firstly, a mathematical optimization model with the objective to maximize the total sale of synthetic coal is established. Then, the model is simplified to another mathematical optimization model with the objective to maximize price of synthetic coal of each stage because of the great difficulty to resolve the model. Thirdly, a genetic algorithm for coordinate mining of multiple mining areas is presented and designed to resolve the simplified model. Finally, the effectiveness of the proposed method is validated by case study.

scholarly journals Optimal re-allocation of mooring areas for yachts

2019 ◽  
Vol 4 (1) ◽  
pp. 94-105
Author(s):  
Shuaian Wang ◽  
Ran Yan ◽  
Lingxiao Wu ◽  
Dong Yang
Keyword(s):  
Optimization Model ◽  
Numerical Experiments ◽  
Design Methodology ◽  
Mathematical Optimization ◽  
Content Type ◽  
Integer Programing ◽  
Proposed Model ◽  
Quantitative Manner ◽  
Mathematical Optimization Model ◽  
The Government

Purpose The purpose of this study is to propose a mathematical optimization model to solve the yacht mooring area re-allocation problem (YMARP). The objective of the problem is to allow the maximum number of yachts to be moored at their ideal mooring areas. Design/methodology/approach In this paper, the YMARP is introduced, formally defined and discussed. The authors develop a 0-1 integer programing optimization model for the problem, which can be solved efficiently using off-shelf solvers. The performance of the model is tested on extensive numerical experiments. Findings The results of the numerical experiments demonstrate that the proposed model can solve the YMARP very efficiently using off-shelf solvers like CPLEX. In particular, problems with up to 30,000 yachts and 400 mooring areas can be solved to optimum within 30 s. Originality/value This study is one of the preliminary studies to consider problems arising in yacht management in a quantitative manner. The proposed model has three main merits. First, it enables the government to better manage yachts and mooring areas. Second, with more yacht owners assigned with ideal mooring areas, the model helps reduce the traveling time of the yacht owners to yacht mooring areas. Third, by reducing the traveling time of the yacht owners, the model contributes to lessening the traffic burden in cities.

The Buckling Optimization on Composite Beam with Hat Stiffener

2014 ◽  
Vol 953-954 ◽  
pp. 1649-1652 ◽  
Author(s):  
Jia Bo Qiu ◽  
Xi Zhu
Keyword(s):  
Genetic Algorithm ◽  
Sensitivity Analysis ◽  
Optimization Model ◽  
Composite Beam ◽  
Mathematical Optimization ◽  
Latin Hypercube Design ◽  
Critical Buckling Load ◽  
Buckling Optimization ◽  
Optimal Latin Hypercube Design ◽  
Mathematical Optimization Model

The paper carried out the buckling optimization on composite beam with hat stiffener by taking ply angle as optimal variables and the critical buckling load (CBL) as the optimal objective. Firstly, the paper established the mathematical optimization model, and then carried out sensitivity analysis of ply angle through Optimal Latin Hypercube Design, finally optimized the design of the layer using Genetic Algorithm. The results show that the CBL of stiffened beam with the optimized ply angle is increased by 64% than that with initial ply angle; CBL can be increased by changing the ply angle, the sheet should adopt the 0° or 90° layer, while the surface and center of stiffener should adopt ±45° layer and the rest should be 0° or 90°.

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