scholarly journals Evaluation Methods of Tax Burden on a Company as a Mean of Financial Optimization Problems Solving

2020 ◽  
Author(s):  
E Fedulova ◽  
O Salkova ◽  
R Zverev
Keyword(s):  
Optimization Problems ◽  
Evaluation Methods ◽  
Tax Burden ◽  
Financial Optimization ◽  
A Company

Enterprise distribution routing optimization with soft time windows based on genetic algorithm

2021 ◽  
pp. 1-11
Author(s):  
Kaixian Gao ◽  
Guohua Yang ◽  
Xiaobo Sun
Keyword(s):  
Genetic Algorithm ◽  
Customer Satisfaction ◽  
Optimization Problems ◽  
Rapid Development ◽  
Time Windows ◽  
Theory And Practice ◽  
Routing Problem ◽  
Logistics Industry ◽  
Routing Optimization ◽  
A Company

With the rapid development of the logistics industry, the demand of customer become higher and higher. The timeliness of distribution becomes one of the important factors that directly affect the profit and customer satisfaction of the enterprise. If the distribution route is planned rationally, the cost can be greatly reduced and the customer satisfaction can be improved. Aiming at the routing problem of A company’s vehicle distribution link, we establish mathematical models based on theory and practice. According to the characteristics of the model, genetic algorithm is selected as the algorithm of path optimization. At the same time, we simulate the actual situation of a company, and use genetic algorithm to plan the calculus. By contrast, the genetic algorithm suitable for solving complex optimization problems, the practicability of genetic algorithm in this design is highlighted. It solves the problem of unreasonable transportation of A company, so as to get faster efficiency and lower cost.

scholarly journals New Safe Approximation of Ambiguous Probabilistic Constraints for Financial Optimization Problem

2019 ◽  
Vol 2019 ◽  
pp. 1-19
Author(s):  
NingNing Du ◽  
Yan-Kui Liu ◽  
Ying Liu
Keyword(s):  
Value At Risk ◽  
Optimization Problem ◽  
Optimization Problems ◽  
Random Perturbation ◽  
Probabilistic Constraints ◽  
Optimization Approach ◽  
Chinese Stock Market ◽  
Robust Solution ◽  
Return Rates ◽  
Financial Optimization

In financial optimization problem, the optimal portfolios usually depend heavily on the distributions of uncertain return rates. When the distributional information about uncertain return rates is partially available, it is important for investors to find a robust solution for immunization against the distribution uncertainty. The main contribution of this paper is to develop an ambiguous value-at-risk (VaR) optimization framework for portfolio selection problems, where the distributions of uncertain return rates are partially available. For tractability consideration, we deal with new safe approximations of ambiguous probabilistic constraints under two types of random perturbation sets and obtain two equivalent tractable formulations of the ambiguous probabilistic constraints. Finally, to demonstrate the potential for solving portfolio optimization problems, we provide a practical example about the Chinese stock market. The advantage of the proposed robust optimization method is also illustrated by comparing it with the existing optimization approach via numerical experiments.

scholarly journals Corporate control and ownership networks

2018 ◽  
Vol 15 (4) ◽  
pp. 86-95 ◽  
Author(s):  
Mirko Di Giacomo ◽  
Marisa Cenci
Keyword(s):  
Control Problem ◽  
Optimization Problems ◽  
Programming Model ◽  
Topological Analysis ◽  
Corporate Control ◽  
Minimum Cost ◽  
Optimization Approach ◽  
Investment Fund ◽  
Indirect Control ◽  
A Company

In this paper, authors consider ownership networks to quantify the ease with which a company can be controlled due to the shareholding relationships in which it is involved. These networks have been usually considered in a descriptive perspective, either to quantify the control exerted by an ultimate shareholder, especially in presence of complex patterns of indirect control, or as a subject of topological analysis. Recently, a new stream of literature arose, solving optimization problems on ownership networks. Among these tools, authors explicitly refer to the Indirect Control Problem (IC) (Martins & Neves, 2017), which determines the minimum cost control strategy of a set of Target company, namely a strategy to build a robust investment fund which includes the corporate control on one or more companies. In this paper, we combine the descriptive and the optimization approach, introducing a linear programming model, namely Cheapest Control Problem (CCP), contributing on both the descriptive and the optimization approach. In particular, authors propose CCP overcome some of the IC main limitations, i.e. the overestimation of control in presence of mutual cross-shareholdings. Furthermore, CCP solutions allow computing three indexes that measure the ease with which a company can be controlled depending on its ownership relationships. Finally, a case study is incorporated to compare IC and CCP solutions, discussing the informative power of the indices introduced.

CONFRONTING MODEL MISSPECIFICATION IN FINANCE: TRACTABLE COLLECTIONS OF SCENARIO PROBABILITY MEASURES FOR ROBUST FINANCIAL OPTIMIZATION PROBLEMS

2002 ◽  
Vol 05 (01) ◽  
pp. 33-54 ◽  
Author(s):  
CRAIG FRIEDMAN
Keyword(s):  
Risk Management ◽  
Asset Allocation ◽  
Financial Models ◽  
Optimization Problems ◽  
Model Misspecification ◽  
Asset Price ◽  
Probability Measures ◽  
Contingent Claim ◽  
Financial Optimization ◽  
Contingent Claim Pricing

Despite the widespread realization that financial models for contingent claim pricing, asset allocation and risk management depend critically on their underlying assumptions, the vast majority of financial models are based on single probability measures. In such models, asset prices are assumed to be random, but asset price probabilities are assumed to be known with certainty, an obviously false assumption. We explore practical methods to specify collections of probability measures for an assortment of important financial problems; we provide practical methods to solve the robust financial optimization problems that arise and, in the process, discover "dangerous" measures.

scholarly journals The Overview of the Evaluation Methods of the Company’s Creditworthiness

2020 ◽  
Vol 7 (4) ◽  
pp. 34-38
Author(s):  
Yu. Tumanov
Keyword(s):  
High Risk ◽  
Evaluation Methods ◽  
A Company

The activity of any commercial organisation is of high risk. It is often connected with the fact that companies tend to take various risks to achieve their own goals for the sake of which they operate and perform their activities. Understanding and determination of whether a company is financially stable require us to conduct the so-called creditworthiness analysis of an entity. Moreover, it is expedient for any profit-making company to analyse and perform monitoring its creditworthiness. All of this makes such a kind of an analysis pretty relevant and useful. This research may be regarded as an attempt to examine theoretical fundamentals and some existing methodologies of creditworthiness analysis.

scholarly journals The price of conserving avian phylogenetic diversity: a global prioritization approach

2015 ◽  
Vol 370 (1662) ◽  
pp. 20140004 ◽  
Author(s):  
Laura A. Nunes ◽  
Samuel T. Turvey ◽  
James Rosindell
Keyword(s):  
Phylogenetic Diversity ◽  
Optimization Problems ◽  
Global Analysis ◽  
Cost Benefit ◽  
Biodiversity Loss ◽  
Current Conservation ◽  
Worst Case ◽  
Financial Optimization ◽  
Spending Patterns ◽  
Global Concern

The combination of rapid biodiversity loss and limited funds available for conservation represents a major global concern. While there are many approaches for conservation prioritization, few are framed as financial optimization problems. We use recently published avian data to conduct a global analysis of the financial resources required to conserve different quantities of phylogenetic diversity (PD). We introduce a new prioritization metric (ADEPD) that After Downlisting a species gives the Expected Phylogenetic Diversity at some future time. Unlike other metrics, ADEPD considers the benefits to future PD associated with downlisting a species (e.g. moving from Endangered to Vulnerable in the International Union for Conservation of Nature Red List). Combining ADEPD scores with data on the financial cost of downlisting different species provides a cost–benefit prioritization approach for conservation. We find that under worst-case spending $3915 can save 1 year of PD, while under optimal spending $1 can preserve over 16.7 years of PD. We find that current conservation spending patterns are only expected to preserve one quarter of the PD that optimal spending could achieve with the same total budget. Maximizing PD is only one approach within the wider goal of biodiversity conservation, but our analysis highlights more generally the danger involved in uninformed spending of limited resources.

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