V. N. Burkov

Network programming technique in project management problems

Network programming technique is developed to derive exact solutions or their lower (upper) bound estimates in multi-extremal (in particular, discrete) optimization problems. The idea of the technique lies in reducing the problem to a superposition of simpler problems. The scheme of reduction is conveniently represented in the form of a network (referred to as network representation), with nodes being the subproblems that enter the superposition. Simple optimization problems are solved at each node, while the solution at the terminal node of the network yields the upper (lower) bound estimate for the initial problem. In the case of tree-shaped network representation, the solution at the terminal node of the network provides the exact solution to the initial optimization problem. This paper overviews application of the network programming technique to several problems of project management.

Application of generalized median voter schemes to designing strategy-proof mechanisms of multicriteria active expertise

Mechanisms of multicriteria active expertise are represented in the form of generalized median voter schemes for collective decision-making in the terms of families of right and left coalition systems. This approach allows for applying the results, obtained in the theory of social choice, to designing strategy-proof mechanisms.

Control Mechanisms in Network Structures

Formulation of the problem of designing the optimal structure of an active system was considered within the framework of the game-theoretical model of interaction of its participants. Solution and the results of studying the control mechanisms in applications such as in-house management and multiagent systems were presented.

Multivariant Active Systems

The concept of multivariant active systems was presented. Basic multivariant structures, facilities, and systems were described. Consideration was given to the heuristic and, in part, strict problems of analysis, design, and realization of the variant-uniting organizational mechanisms integrated with the functional and auxiliary subsystems of the multivariant active systems including appropriate structural, procedural, and algorithmic developments. Particular multivariant active systems for education, industries, and industrial research were described.

Methodology and Technology of Control Systems Development

The development of new information technologies aimed at increasing the efficiency of activities in various fields is one of the most urgent tasks today. The leading Russian experts in strategic management have developed information technologies to improve the efficiency of activities in virtually all spheres of social and economic systems. Such technologies include the technology of working out development management systems (DMS). The research methodology consists of elements of control theory, systems theory, and system analysis methods. The main results of the research related to three models. The first model is related to risk management based on qualitative assessments. The second model is related to the synergetic effect that occurs when a pair of projects is included in the development program. The third model is devoted to the formation of the program calendar plan by the criterion of minimizing lost profits. The proposed system is successfully applied to the development of territorial development management systems, enterprises, personnel competence level and others. In the DMS technology, several mathematical models and methods are used. Basically, there is the “cost-effect” method and financial models. The chapter attempts to supplement the technology of DMS with a number of information technologies on the basis of mathematical models, the inclusion of which in the DMS technology increases the effectiveness of its application.

Risk Level Control in Ecological-Economic Systems

This chapter considers general problems of risk level control in ecologicaleconomic systems. Section 1.1 describes environmental and anthropogenic risks and presents the structure of possible losses due to emergency situations. Next, Section 1.2 overviews risk level assessment methods. And finally, Section 1.3 is dedicated to optimization mechanisms for regional risk level reduction programs.

Control Mechanisms at the Level of Regional Authorities

This chapter adopts the following structure of material presentation. For efficiency assessment of environmental safety control mechanisms, we introduce a control model for regional environmental safety level (Section 3.1). Subsequent analysis focuses on models of risk payment mechanisms (Section 3.2), financing mechanisms for risk level reduction (Section 3.3), costs compensation mechanisms for risk level reduction (Section 3.4), sales mechanisms for risk level quotas (Section 3.5), insurance mechanisms (Section 3.6), economic motivation mechanisms (Section 3.7), and mechanisms for authorities’ interests coordination (Section 3.8).

Control Mechanisms at the Level of Industrial Enterprises

In the sequel, we consider the models of a region with n business agents (e.g., industrial enterprises). Their activity may cause an emergency situation (ES), thereby reducing the level of regional safety (increasing the level of regional risks).

Simulation Models for Control Mechanisms in Ecological-Economic Systems

Chapters 2 and 3 have been focused on the “theoretical” study of control mechanisms in ecological-economic systems. In contrast, the current chapter presents the results of “experiments,” viz., business and simulation games. Section 4.1 provides a qualitative discussion of gaming simulation as an analysis method for safety control mechanisms. Sections 4.2-4.6 describe necessary preparations and results of business games for risk payment mechanisms, incentive mechanisms for risk level reduction, financing mechanisms for risk level reduction, costs compensation mechanisms for risk level reduction, and sales mechanisms for risk level quotas, respectively.

The network programming method in control over target programs

We consider the problem of optimizing programs with respect to cost. The state of a program is defined via several goals (criteria) based on a complex evaluation system. For each goal, there exist several projects that contribute to achieving this goal. A number of projects contributes to several goals (multipurpose projects). To solve the problem, we propose two methods. One is based on enumerating all possible ways to include multipurpose projects into the program. The other is based on a network programming technique. We give results of numerical experiments that compare these approaches.