Optimal adaptive control of business planning processes based on network economic and mathematical modeling

The article discusses the problem of optimizing the adaptive control of business planning processes by an economic entity. The results of the work are based on a new method of network formalization and optimization of adaptive project management, using network economic and mathematical modeling and the principles of adaptive control. The paper describes a new optimization network economicand mathematical model. This model takes into account the possibilities of monitoring the states ofthe process under consideration and adaptive control of the implementation of a business project. Within the framework of the formed network model, a new method for solving the task of network formalization and optimization of adaptive control of business planning processes is proposed. When implementing the proposed method, a strategy for optimal adaptive control of business planning processes is formed. On its basis, the optimal time for the implementation of a business project and the optimal schedule for its implementation in general are calculated. The article describes the practical application of the proposed method for solving the considered optimization problem on a specific example of the implementation of business planning processes in the development of new dishes at a public catering enterprise. The results obtained in the work show the sufficient efficiency of the developed new method of formalization and optimization of adaptive control of business planning processes. Further development of this area of research can be associated with the development of an intelligent computer system for optimizing the adaptive control of business planning processes and the creation of appropriate tools to support the adoption of management decisions by business entities during their implementation. © 2020 Author(s).This work was supported by the Russian Basic Research Foundation, project no.18-01-00544 “Problems of attainability, control, estimation in dynamical systems with impulse control and uncertainty.

Efficient monitoring and control in intangibles-driven economies: is full independence always required?

The current crisis puts at issue the self-regulated market system of monitoring and control. Claims for restoring the proper functioning of market economies in general, and financial markets in particular, call for either establishing new sets of rules or creating new supervising authorities. Both claims rely on the received mantra of full independence that applies whenever control is concerned. However, our analysis pays attention to a neglected aspect of monitoring and control, which requires the capability to discovering and understanding flaws in and dangers from the inner congeries of the business affair under examination. Arguably, this businessspecific expertise and independence trade off. To overcome this problem, an optimal share of non-independent controllers may be chosen from or appointed by stakeholding constituencies of the business affair. They can provide proficient monitoring and control without colluding, in principle, with executive managers of the activity to be controlled

Network models for solving the problem of multicriterial adaptive optimization of investment projects control with several acceptable technologies

This paper discusses the problem of multicriterial adaptive optimization the control of investment projects in the presence of several technologies. On the basis of network modeling proposed a new economic and mathematical model and a method for solving the problem of multicriterial adaptive optimization the control of investment projects in the presence of several technologies. Network economic and mathematical modeling allows you to determine the optimal time and calendar schedule for the implementation of the investment project and serves as an instrument to increase the economic potential and competitiveness of the enterprise. On a meaningful practical example, the processes of forming network models are shown, including the definition of the sequence of actions of a particular investment projecting process, the network-based work schedules are constructed. The calculation of the parameters of network models is carried out. Optimal (critical) paths have been formed and the optimal time for implementing the chosen technologies of the investment project has been calculated. It also shows the selection of the optimal technology from a set of possible technologies for project implementation, taking into account the time and cost of the work. The proposed model and method for solving the problem of managing investment projects can serve as a basis for the development, creation and application of appropriate computer information systems to support the adoption of managerial decisions by business people. © 2017 Author(s).This work was supported by the Russian Basic Research Foundation, project no. 17-01-00315

Operational risk management and new computational needs in banks

Basel II banking regulation introduces new needs for computational schemes. They involve both optimal stochastic control, and large scale simulations of decision processes of preventing low-frequency high loss-impact events. This paper will first state the problem and present its parameters. It then spells out the equations that represent a rational risk management behavior and link together the variables: Levy processes are used to model operational risk losses, where calibration by historical loss databases is possible ; where it is not the case, qualitative variables such as quality of business environment and internal controls can provide both costs-side and profits-side impacts. Among other control variables are business growth rate, and efficiency of risk mitigation. The economic value of a policy is maximized by resolving the resulting Hamilton-Jacobi-Bellman type equation. Computational complexity arises from embedded interactions between 3 levels: * Programming global optimal dynamic expenditures budget in Basel II context, * Arbitraging between the cost of risk-reduction policies (as measured by organizational qualitative scorecards and insurance buying) and the impact of incurred losses themselves. This implies modeling the efficiency of the process through which forward-looking measures of threats minimization, can actually reduce stochastic losses, * And optimal allocation according to profitability across subsidiaries and business lines. The paper next reviews the different types of approaches that can be envisaged in deriving a sound budgetary policy solution for operational risk management, based on this HJB equation. It is argued that while this complex, high dimensional problem can be resolved by taking some usual simplifications (Galerkin approach, imposing Merton form solutions, viscosity approach, ad hoc utility functions that provide closed form solutions, etc.) , the main interest of this model lies in exploring the scenarios in an adaptive learning framework ( MDP, partially observed MDP, Q-learning, neuro-dynamic programming, greedy algorithm, etc.). This makes more sense from a management point of view, and solutions are more easily communicated to, and accepted by, the operational level staff in banks through the explicit scenarios that can be derived. This kind of approach combines different computational techniques such as POMDP, stochastic control theory and learning algorithms under uncertainty and incomplete information. The paper concludes by presenting the benefits of such a consistent computational approach to managing budgets, as opposed to a policy of operational risk management made up from disconnected expenditures. Such consistency satisfies the qualifying criteria for banks to apply for the AMA (Advanced Measurement Approach) that will allow large economies of regulatory capital charge under Basel II Accord.REGULAR - Operational risk management, HJB equation, Levy processes, budget optimization, capital allocation

Human sit-to-stand transfer modeling towards intuitive and biologically-inspired robot assistance

© 2016, Springer Science+Business Media New York. Sit-to-stand (STS) transfers are a common human task which involves complex sensorimotor processes to control the highly nonlinear musculoskeletal system. In this paper, typical unassisted and assisted human STS transfers are formulated as optimal feedback control problem that finds a compromise between task end-point accuracy, human balance, energy consumption, smoothness of motion and control and takes further human biomechanical control constraints into account. Differential dynamic programming is employed, which allows taking the full, nonlinear human dynamics into consideration. The biomechanical dynamics of the human is modeled by a six link rigid body including leg, trunk and arm segments. Accuracy of the proposed modelling approach is evaluated for different human healthy and patient/elderly subjects by comparing simulations and experimentally collected data. Acceptable model accuracy is achieved with a generic set of constant weights that prioritize the different criteria. Finally, the proposed STS model is used to determine optimal assistive strategies suitable for either a person with specific body segment weakness or a more general weakness. These strategies are implemented on a robotic mobility assistant and are intensively evaluated by 33 elderlies, mostly not able to perform unassisted STS transfers. The validation results show a promising STS transfer success rate and overall user satisfaction

Dynamic optimization of a gas-liquid reactor

The final publication is available at Springer via http://dx.doi.org/10.1007/s10910-011-9941-1A dynamic gas-liquid transfer model without chemical reaction based on unsteady film theory is considered. In this case, the mathematical model presented for gas-liquid mass-transfer processes is based on mass balances of the transferred substance in both phases. The identificability property of this model is studied in order to confirm the possible identifiable parameters of the model from a given set of experimental data. For that, a different modeled of the system is given. A procedure for the identification is proposed. On the other hand, the aim of this work is to solve the quadratic optimal control problem, using an explicit representation of the model. The problem includes some results on controllability, observability and stability criteria and the relation between these properties and the parameters of the model. Using the optimal control problem we study the stability of the system and show how the choice of the weighting matrices can improve the behavior of the system but with an increase of the energy control cost. © 2011 Springer Science+Business Media, LLC.This work has been partially supported by PAID-05-10-003-295 and by MTM2010-18228.Cantó Colomina, B.; Cardona Navarrete, SC.; Coll, C.; Navarro-Laboulais, J.; Sánchez, E. (2012). Dynamic optimization of a gas-liquid reactor. Journal of Mathematical Chemistry. 50(2):381-393. https://doi.org/10.1007/s10910-011-9941-1S381393502Bayón L., Grau J.M., Ruiz M.M., Suárez P.M.: Initial guess of the solution of dynamic optimization of chemical processes. J. Math. Chem. Model. 48, 28–37 (2010)Ben-Zvi A., McLellan P.J., McAuley K.B.: Ind. Eng. Chem. Res. 42, 6607–6618 (2003)Cantó B., Coll C., Sánchez E.: Structural identifiability of a model of dialysis. Math. Comp. Model. 50, 733–737 (2009)Cantó B., Coll C., Sánchez E.: Identifiability of a class of discretized linear partial differential algebraic equations. Math. Probl. Eng. 2011, 1–12 (2011)Craciun G., Pantea C.: Identifiability of chemical reaction networks. J. Math. Chem. 44, 244–259 (2008)Dai L.: Descriptor Control Systems. Springer, New York (1989)Deckwer W.D.: Bubble Column Reactors. Wiley, Chichester (1992)Kantarci N., Borak F., Ulgen K.O.: Bubble column reactors. Proc. Biochem. 40(7), 2263–2283 (2005)Kawakernaak H., Sivan R.: Linear Optimal Control Systems. Wiley-Interscience, New York (1972)Kuo B.C.: Automatic Control Systems, 6th edn. Prentice-Hall, Englewood Cliffs (1991)Navarro-Laboulais J., Cardona S.C., Torregrosa J.I., Abad A., López F.: Practical identifiability analysis in dynamic gas-liquid reactors. Optimal experimental design for mass-transfer parameters determination. Comp. Chem. Eng. 32, 2382–2394 (2008)Navarro-Laboulais J., López F., Torregrosa J.I., Cardona S.C., Abad A.: Transient response, model structure and systematic errors in hybrid respirometers: structural identifiabilit analysis based on OUR and DO measurements. J. Math. Chem. 44(4), 969–990 (2007)Patel R., Munro N.: Multivariable Systen. Theory and Design. Pergamon Press, New York (1982)Sondergeld K.: A generalization of the Routh–Hurwitz stability criteria and a application to a problem in robust controller design. IEEE Trans. Automat. Contr. AC-28(10), 965–970 (1983

Reinforcement Learning Based Production Control of Semi-automated Manufacturing Systems

In an environment which is marked by an increasing speed of changes, industrial companies have to be able to quickly adapt to new market demands and innovative technologies. This leads to a need for continuous adaption of existing production systems and the optimization of their production control. To tackle this problem digitalization of production systems has become essential for new and existing systems. Digital twins based on simulations of real production systems allow the simplification of analysis processes and, thus, a better understanding of the systems, which leads to broad optimization possibilities. In parallel, machine learning methods can be integrated to process the numerical data and discover new production control strategies. In this work, these two methods are combined to derive a production control logic in a semi-automated production system based on the chaku-chaku principle. A reinforcement learning method is integrated into the digital twin to autonomously learn a superior production control logic for the distribution of tasks between the different workers on a production line. By analyzing the influence of different reward shaping and hyper-parameter optimization on the quality and stability of the results obtained, the use of a well-configured policy-based algorithm enables an efficient management of the workers and the deduction of an optimal production control logic for the production system. The algorithm manages to define a control logic that leads to an increase in productivity while having a stable task assignment so that a transfer to daily business is possible. The approach is validated in the digital twin of a real assembly line of an automotive supplier. The results obtained suggest a new approach to optimizing production control in production lines. Production control shall be centered directly on the workers’ routines and controlled by artificial intelligence infused with a global overview of the entire production system

Identity Management

Identity Management (IdM) has been a serious problem since the establishment of the Internet as a global network used for business and pleasure. Originally identified in a Peter Steiners’ 1993 New Yorker cartoon “On the Internet nobody knows you’re a dog”, the problem is over 15 years old. Yet, little progress has been made towards an optimal solution. In its early stages, IdM was designed to address the problem of controlling access to resources and managing the matching of capabilities with people in well defined situations (e.g., Access Control Lists). In today’s computing environment, IdM involves a variety of user centric, distinct, personal forms of digital identities. Starting with the basics of traditional access control often assimilated to “directory entries” (i.e., ID, password and capability) IdM is generalized to the global networked society we now live in. With the advent Inter-organizational systems (IOS), social networks, e-commerce, m-commerce, service oriented computing and automated agents (such as botnets), the characteristics of IdM evolved to include people, devices, and services. In addition, as the complexity of IdM increases so did related social issues such as legitimacy, authoritativeness, privacy rights, personal information protection as well as broader problems of cyber predators and threats. The tutorial addresses the following IdM topics: history and background (access control), what is IdM, technical challenges, social issues, life cycle, standards, research projects, industry initiatives, paradigms, vendor solutions, implementation challenges, emerging trends, and research concepts

Air traffic conflict resolution via light propagation modeling

The analysis of air traffic growth expects a doubling in the flights number over the next 20 years. The Air Traffic Management (ATM) will therefore have to absorb this additional burden and to increase the airspace capacity, while ensuring at least equivalent standards of safety. The European project SESAR was initiated to propose solutions to this problem. It relies on a new concept of air traffic control, known as 4D (3D + time) trajectory planning, which consists in exploiting the new Flight Management System (FMS) abilities that ensure that the aircraft is at a given position at a given moment. For each flight, a reference trajectory, called Reference Business Trajectory (RBT), is requested by the operating airline. During the flight, conflict situations may nevertheless occur, in which two or several aircraft can dangerously approach each other. In this case, it is necessary to modify one or more trajectories to ensure that minimum separation standards (currently 5 Nm horizontally and 1000 ft vertically) are still satisfied. Moreover, it is desirable that proposed new trajectories deviate as little as possible from RBTs. Several methods have been tested to find an optimal solution to address this problem including genetic algorithm[1] and navigation function based approach[2]. The first approach can not guarantee a feasible (conflict-free) solution for a given time computing. The second one does not take into account the constraints imposed by ATM, such as bounded velocity