scholarly journals Development of a computer intelligent system for optimizing adaptive control of business planning processes

2021 ◽  
Vol 1794 (1) ◽  
pp. 012005
Author(s):  
A F Shorikov ◽  
E V Butsenko
Author(s):  
Andrey Shorikov

The article is devoted to the application of economic and mathematical models of business planning management based on the use of the feedback principle. As the objective function (evaluation toolkit) of the task, the value of the execution time of the entire business project, which must be minimized, is considered. To solve this problem, it is proposed to form a class of admissible strategies for optimal adaptive control of the implementation process; as well as a specific business project using network economic and mathematical modeling is worked out. Within the limits of these strategies, the method of achieving optimal self-adjusting control of business planning processes is determined, the optimal execution time and the optimal timetable for the implementation of the project are determined. The main feature of the proposed new method is the ability to take into account the real conditions for the implementation works of the concrete project, which makes it possible to timely adjust the process of management of business planning and prevent disruptions in its implementation. This method also serves as the basis for constructing numerical algorithms for the development and creating the automated systems for realization of optimal adaptive control of business planning processes. The results obtained are illustrated on a specific business project for opening a public catering enterprise and show a high degree of efficiency in using the new method.


2020 ◽  
Vol 15 (89) ◽  
pp. 9-28
Author(s):  
Andrey F. Shorikov ◽  
◽  
Elena V. Butsenko ◽  

The article describes the functionality developed by the authors of an intelligent software system for optimizing adaptive control of business planning processes in the face of uncertainty. The results are based on a new method for optimizing adaptive project management using network economic and mathematical modeling. Based on this method, a methodology has been developed for solving the problem of optimizing adaptive control of business planning processes, which in the proposed intelligent software decision support system uses a block containing an adaptive control optimization model. As the objective function (evaluation functional) in the method used, the value of the length of the time period for the execution of the business plan, which needs to be minimized, is considered. The method used allows you to create a class of acceptable strategies for adaptive control of the implementation process for the business plan in question. Within the framework of this class of strategies, an optimal adaptive control strategy for the implementation of business planning processes is formed, the optimal time for its implementation and the optimal schedule for implementing the business plan as a whole, and the corresponding optimal adaptive control strategies are calculated. Application of the proposed new method in an intelligent software system allows for feedback and optimal time for the implementation of the business project as a whole. The developed intelligent system is designed to automate the modeling of business planning processes and optimize adaptive decision-making control during their implementation on the basis of network economic and mathematical modeling, as well as methods and tools for developing intelligent soft systems. The created system takes into account the existing specific technical and economic conditions and information support. The results obtained in this work can serve as the basis for creating intelligent instrumental systems for supporting managerial decision-making in the implementation of business planning processes in the face of information uncertainty and risks.


2011 ◽  
Vol 16 (02) ◽  
pp. 213-226 ◽  
Author(s):  
CRAIG E. ARMSTRONG

Studies of the relationship between gender and entrepreneurship have shown that men are significantly more likely to start a new business than women. Because an individual's entrepreneurial intentions are shaped by the perceived feasibility and desirability of an entrepreneurial opportunity, these results have generally emphasized how men perceive themselves as more capable of pursuing entrepreneurial opportunities than women. In this study, men have a higher level of self-efficacy than do women regarding entrepreneurial abilities. At the same time, the higher levels of involvement in business planning processes caused women to have a higher sense of ownership in the plan than did men. This sense of ownership is positively and significantly related to the perceived likelihood of success of the new venture. The findings of this study suggest women adopt certain roles and affects in the development of entrepreneurial opportunities that provide alternative explanations to the beliefs-attitudes-intentions-behavior model of intentionality. The roles and affects women adopt during new venture planning may give them superior insights into the likelihood of success of the new venture.


2020 ◽  
Author(s):  
Emiel Cracco ◽  
Senne Braem ◽  
Marcel Brass

A key prediction of ideomotor theories is that action perception relies on the same mechanisms as action planning. While this prediction has received support from studies investigating action perception in one-on-one situations, situations with multiple actors pose a challenge because in order to co-represent multiple observed actions, observers have to represent more actions in their motor system than they can physically execute. If representing multiple observed actions, like representing individual observed actions, recycles action planning processes, this should lead to response conflict by observation. In 5 experiments, we tested this hypothesis by investigating whether simply seeing two conflicting actions is sufficient to elicit response conflict and therefore adaptive control, in the same way as planning conflicting actions does. Experiments 1-3 provided meta-analytical evidence (N = 262) that seeing two conflicting gestures triggers a reverse congruency sequence effect on a subsequent, unrelated prime-probe task. Experiment 4 (N = 250) replicated this finding in a high-powered study. Finally, Experiment 5 (N = 253) revealed that the same effect was not present when using unfolding abstract shapes instead of moving hands. Together, these experiments show that not just planning but also seeing two conflicting actions elicits adaptive control and provide initial evidence that this is driven by motor conflict. These findings have important implications both for theories of action representation and research on cognitive control.


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