Research of Mathematical Model of Insurance Company in the Form of Queueing System in a Random Environment

2017 ◽  
pp. 204-214 ◽  
Author(s):  
Diana Dammer
Keyword(s):  
Mathematical Model ◽  
Random Environment ◽  
Queueing System ◽  
Insurance Company

scholarly journals INCREASING THE COMPETITIVENESS OF INSURANCE COMPANY PRODUCTS AND SERVICES USING ECONOMIC AND MATHEMATICAL MODELING METHODS

2021 ◽  
Author(s):  
Mykhailo Demydenko ◽  
Ihor Pistunov
Keyword(s):  
Mathematical Model ◽  
Social Activity ◽  
Insurance Companies ◽  
Comprehensive System ◽  
Insurance Company ◽  
Competitive Advantages ◽  
Insurance Policy ◽  
Insurance Policies ◽  
The Impact

The competitiveness of an insurance company depends on the competitiveness of the products and services it introduces in the market. The competitive advantages of the insurance company are expressed in the attractiveness and competitiveness of insurance policies. An economic and mathematical model of increasing the competitiveness of the insurance company is proposed, which allows to calculate the integrated indicator of competitiveness of the insurance policy based on a comprehensive system of indicators characterizing the reliability of the insurance company, quality of its services, competitiveness, social activity. To analyze the impact of these indicators on the competitiveness of the insurance policy and identify areas for improving the efficiency and competitiveness of the insurance company. The competitiveness of an insurance company depends on the competitiveness of the products and services it introduces in the market. The assessment of the quality of insurance company services is compliance with the needs, requirements, and insurance interests of customers. This assessment is performed each time an individual client chooses to cooperate with an insurance company that meets his insurance interests and wishes. Therefore, the overall competitiveness of the enterprise depends on the competitiveness of products and services offered on the market. The competitive advantages of the insurance company are expressed in the attractiveness and competitiveness of insurance policies. The insurance market in recent years has shown consistently high growth, which makes it attractive for doing business. In these conditions, the task of modeling the activities of the insurance company in a highly competitive market environment becomes relevant. A mathematical model of increasing the competitiveness of the insurance company is proposed, which allows to calculate the integrated indicator of competitiveness of the insurance policy based on a comprehensive system of indicators characterizing the reliability of the insurance company, quality of its services, competitiveness, social activity. With the proposed model, insurance companies can objectively assess their weaknesses and strengths to ensure continuous growth and decent competition in a competitive market environment. The model allows you to select performance indicators and perform modeling and determine the consequences of changes in this indicator, analyze the impact of these indicators on the competitiveness of insurance policies and identify areas for improving the efficiency and competitiveness of the insurance company. By conducting such experiments, insurance companies can make more informed choices and decisions, analyze areas of competitiveness, and more efficiently allocate resources.

scholarly journals Two-Sex Branching Processes with Offspring and Mating in a Random Environment

2009 ◽  
Vol 46 (04) ◽  
pp. 993-1004
Author(s):  
S. Ma ◽  
M. Molina
Keyword(s):  
Mathematical Model ◽  
Probability Distribution ◽  
Discrete Time ◽  
Random Environment ◽  
Generating Functions ◽  
Branching Processes ◽  
Random Vectors ◽  
Environmental Process ◽  
Mating Function ◽  
The Mathematical Model

We introduce a class of discrete-time two-sex branching processes where the offspring probability distribution and the mating function are governed by an environmental process. It is assumed that the environmental process is formed by independent but not necessarily identically distributed random vectors. For such a class, we determine some relationships among the probability generating functions involved in the mathematical model and derive expressions for the main moments. Also, by considering different probabilistic approaches we establish several results concerning the extinction probability. A simulated example is presented as an illustration.

scholarly journals The M/M/C queueing system in a random environment

2016 ◽  
Vol 436 (1) ◽  
pp. 556-567 ◽  
Author(s):  
Zaiming Liu ◽  
Senlin Yu
Keyword(s):  
Random Environment ◽  
Queueing System

The retrial queueing system operating in random environment

2007 ◽  
Vol 137 (12) ◽  
pp. 3904-3916 ◽  
Author(s):  
Che Soong Kim ◽  
Valentina Klimenok ◽  
Sang Cheon Lee ◽  
Alexander Dudin
Keyword(s):  
Random Environment ◽  
Queueing System ◽  
Retrial Queueing System ◽  
Retrial Queueing ◽  
System Operating

scholarly journals Mathematical Model of One-Channel Queueing System with Two-Stage Remand Arrival

2020 ◽  
pp. 54-61
Author(s):  
L. A. Votiakova ◽  
◽  
O. S. Turzhanska ◽  
O. A. Nazarchuk ◽  
◽  
...  
Keyword(s):  
Mathematical Model ◽  
Queueing System ◽  
Two Stage

scholarly journals Mathematical Models of Mb/M/1 Bulk Arrival Queueing System

2014 ◽  
Vol 10 (1) ◽  
pp. 184-191 ◽  
Author(s):  
Sushil Ghimire ◽  
R. P. Ghimire ◽  
Gyan Bahadur Thapa
Keyword(s):  
Mathematical Model ◽  
Function Method ◽  
Queueing System ◽  
Batch Size ◽  
Queueing Model ◽  
Mean Waiting Time ◽  
Bulk Arrival ◽  
Number Of Customers ◽  
The Mathematical Model ◽  
Mean Time

 This paper deals with the study of bulk queueing model with the fixed batch size ‘b’ and customers arrive to the system with Poisson fashion with the rate λ and are severed exponentially with the rate μ. On formulating the mathematical model, we obtain the expressions for mean waiting time in the queue, mean time spent in the system, mean number of customers/work pieces in the queue and in the system by using generating function method. Some numerical illustrations are also obtained by using MATLAB-7 so as to show the applicability of the model under study.DOI: http://dx.doi.org/10.3126/jie.v10i1.10899Journal of the Institute of Engineering, Vol. 10, No. 1, 2014, pp. 184–191

Erlang loss queueing system with batch arrivals operating in a random environment

2009 ◽  
Vol 36 (3) ◽  
pp. 674-697 ◽  
Author(s):  
Che Soong Kim ◽  
Alexander Dudin ◽  
Valentina Klimenok ◽  
Valentina Khramova
Keyword(s):  
Random Environment ◽  
Queueing System ◽  
Batch Arrivals ◽  
Erlang Loss
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