Моделирование САУ в пакете SCILAB: методические указания к практическим занятиям по курсу «Основы теории управления»
This is the first book that presents basic ideas of optimization methods that are applicable to strategic planning and operations management, particularly in the field of transportation. The material of the book covers almost all parts of optimization and is a unique reference work in the field of operations research. The author has written an invaluable manual for students who study optimization methods and their applications in strategic planning and operations management. He describes the ideas behind the methods (with which the study of the methods usually starts) and substantially facilitates further study of the methods using original scientific articles rather than just textbooks. The book is also designed to be a manual for those specialists who work in the field of management and who recognize optimization as the powerful tool for numerical analysis of the potential and of the competitiveness of enterprises. A special chapter contains the basic mathematical notation and concepts useful for understanding the book and covers all the necessary mathematical information.
The paper focuses on the questions of analysis, selection and monitoring of management systems development programs, relying on comparison of the program related expenditures and dynamics of the system’s maturity level, using simulation modeling. In this regard, integrated indicators, which characterize effectiveness of the development program, its financial aspects, as well as its efficiency and duration, are considered. Specific features related with of calculation of the development program integrated indicators using the results of simulation modeling and appropriate statistical metrics are disclosed.
This paper presents the results of studies aimed at effectiveness analysis of the research centre. The study focuses on the process of self-organization of the project team (a group of co-authors) for the project implementation (writing a scientific article). Initiative to create a team comes from one of its members. The paper describes the formal model, based on a competence approach, which considers the types of tasks to be solved and the necessary skills of the staff. The paper also presents the results of simulation in the AnyLogic environment and problems up to further research.
The competency profile of each employee is a vector where each coordinate describes the level of his possession of the corresponding skill. The competency profile of the team is a vector, obtained as a result of a simple addition of competency profiles of participants. The proposed model assumes that each task requires a certain set of competencies and that the list of competencies and the level of experience are the criteria for deciding whether to join the team. The logic of decision making at various stages of team creating is modelled by deterministic Boolean functions. At each step of the modelling, the next employee is chosen randomly. To calibrate the team member competency profile the internal data of the employee’s qualifications of the Gazpromneft Research Center was used. The constructed model is the basis for further studies of the process of creations and functioning of project teams in the scientific environment and for the development of a methodology for assessing the effectiveness of the research teams working. It allows predicting the need for personnel with different competencies, plans activities to improve the skills of employees and strengthen communication in the team.
This article presents a new approach to designing decision-making systems for socio-economic and ecological planning using parallel real-coded genetic algorithms (RCGAs), aggregated with simulation models by objective functions. A feature of this approach is the use of special agent-processes, which are autonomous genetic algorithms (GAs) acting synchronously in parallel streams and exchanging periodically by the best potential decisions. This allows us to overcome the premature convergence problem in local extremums. In addition, it was shown that the combined use of different crossover and mutation operators significantly improves the time efficiency of RCGAs, as well as the quality of the decisions obtained (proximity to optimum), providing a more diverse population of potential decisions (individuals). In this paper, several suggested crossover and mutation operators are used, in particular, a modified simulated binary crossover (MSBX) and scalable uniform mutation operator (SUM), which is based on quantization of the feasible region of the search space (dividing the feasible region on small subranges with equal lengths) while taking into account the common amount of interacting agent-processes and the maximum number of internal iterations of GAs forming potential decisions through selection, crossover and mutation. Such a functional dependence of the parameters of heuristic operators on the corresponding process characteristics, aggregated with the combined probabilistic use of various crossover and mutation operators, makes it possible to get maximum effect from the multi-processes architecture. As a result, the computational possibilities of RCGAs for solving large-scale optimization problems (hundreds and thousands of decision variables, multiple objective functions) become dependent only on the physical characteristics of the existing computing clusters. This makes it possible to efficiently use supercomputer technologies. An important advantage of the proposed system is the implemented integration between the developed parallel RCGA (implemented in C++ and MPI) and the simulation modelling system AnyLogic (Java) using JNI technology. Such an approach allows one to synthesize real world optimization problems in decision-making systems of socio-economic and ecological planning, using simulation methods supported by AnyLogic. The result is an effective solution to singleobjective and multi-objective optimization tasks of large dimension, in which the objective functionals are the result of simulation modeling and cannot be obtained analytically.
Russian mining industry experiences a rapid growth providing an attractive market for suppliers of mining equipment. However, it's a customer-dominated market. The customers set stringent requirements for the initial equipment supply, as well as for the after-sale service and spare parts supply. The manufacturers of mining equipment are thus facing the need to rigorously analyze their supply chain, to develop a reasonable customer service policy and to adjust the supply chain to meet the requirements of the service policy. To fulfill the after-sale maintenance requirements, the manufacturers must stock spare parts within the supply chain and to design inventory control policies. This paper presents an agent-based simulation approach for estimation of the supply chain's key performance indicators and to explore the service - cost trade-off. The conceptual model and the description of its implementation in Anylogic 8.4 software are provided. A case-study of a global mining equipment manufacturer's branch operating in Russia is described. The model is used to estimate the inventory control policy parameters required to meet the target customer service level, to compare make-to-order against make-to-stock supply strategies, as well as to explore the service level - cost trade-off.