scholarly journals Description of approaches to the study of decentralized complex systems in the management of the regional construction cluster

2018 ◽  
Vol 251 ◽  
pp. 05008
Author(s):  
Dmitrii Anufriev ◽  
Artem Holodov
Keyword(s):  
Complex System ◽  
Complex Systems ◽  
System Dynamics ◽  
Simulation Model ◽  
Economic System ◽  
Discrete Event ◽  
Queuing System ◽  
Queuing Network ◽  
Centralized Management ◽  
Probabilistic Structure

Regional construction cluster, which is considered as a decentralized socio-economic system, territorially localized within the region, consisting of interconnected enterprises of construction and related industries. Development of a method for centralized management of a complex socio-economic system based on the integration of simulation approaches. Approaches are considered that allow the transition from consideration of a decentralized complex system to the management of a centralized structure through the introduction of image agents and the formation of a multiphase queuing network, where the four-channel queuing system with expectations is considered as the phase. The structure of the simulation model is presented, which makes it possible to model the functionality of the regional construction cluster. The approaches to integration of the agent approach with modules of system dynamics and modules implementing the discrete-event approach for simulation of business pro-cesses in a complex socio-economic system that take into account the probabilistic structure of the emerging processes are considered in the article.

Governing Dynamics in Complex Systems using Big Data Information

DIALOGO ◽  
2021 ◽  
Vol 8 (1) ◽  
pp. 43-54
Author(s):  
Catalin Nutu
Keyword(s):  
Complex System ◽  
Big Data ◽  
Complex Systems ◽  
Economic System ◽  
Environmental Issues ◽  
Sustainable Growth ◽  
Accurate Estimation ◽  
Economic Systems ◽  
Made In

The paper is presenting different dynamics of an economic complex system, based on certain assumptions made within each of the presented models in the paper. The assumptions used are allowing estimating and forecasting the evolution of the respective complex economic system. This estimation can be made in the “classical” way, which is to say without the use of big data, in which case the results are more prone to errors, or with the use of the recordings of big data, which delivers a much more accurate estimation of the evolution within the complex systems. Throughout the paper the term “with sustainable growth” is used with the meaning of “ecological growth” and it refers to durable economic systems where the environmental issues are taken into consideration, whereas the term “without sustainable growth” or “conventional growth” refers to the economic systems where the environmental issues are not taken into account.

Complex System Design Verification Using Assumption Generation

2013 ◽  
Author(s):  
Hoda Mehrpouyan ◽  
Dimitra Giannakopoulou ◽  
Guillaume Brat ◽  
Irem Y. Tumer ◽  
Chris Hoyle
Keyword(s):  
Complex System ◽  
Complex Systems ◽  
System Design ◽  
Discrete Event ◽  
System Level ◽  
Design Verification ◽  
Safety Properties ◽  
Compositional Model ◽  
Counter Example ◽  
Verification Techniques

In the era of large complex systems with continuous and discrete event components, it is critical to establish a complete design verification strategy to determine whether a system satisfies certain safety properties. However, traditional approaches for the verification of such a complex system lack the ability to take into account all possible system states, efficiently model all component interactions, and accurately quantify the risks and uncertainties. This paper presents a methodology for system-level design of complex systems verification based on compositional model checking. This methodology relies on assumption generation and on the domain independent compositional rules for correctness proof of the design of physical systems. The objective is to present a case study for applying the existing automated compositional verification techniques and observing the characteristics of the verification model. The main advantage of this method is that it enables the designer to verify the safety properties of the system without requiring the detail knowledge of the internal actions of the system. The under-approximate context model of the system design is constructed and, in an iterative approach, its safety properties are analyzed until a violation of a property is found and an execution trace called a counter example is produced. In the case of safety requirements violation, the early generation of counter examples leads to faster design verification.

Learning and Education Experience in System Dynamics of Management Students

2017 ◽  
Vol 9 (2) ◽  
pp. 21-38 ◽  
Author(s):  
Miroljub Kljajić ◽  
Andrej Škraba ◽  
Mirjana Kljajić Borštnar
Keyword(s):  
System Dynamics ◽  
Simulation Model ◽  
Discrete Event ◽  
Modelling And Simulation ◽  
Managerial Decision ◽  
Final Grade ◽  
Continuous Simulation ◽  
Event Simulation ◽  
Education Experience ◽  
Management Students

Article describes experiences in the teaching of a modelling and simulation course for students at Faculty of Organizational Sciences. The course consists of time-continuous simulation based on System Dynamics (SD) and discrete event simulation (DES). It is held in the 3rd year of studies, at which point students have taken courses in mathematics, statistics, theory of systems, as well as organizational and economic courses. The final grade for the course is derived from the student's project and written exam. Students took part in an experiment where they had to solve a managerial decision problem supported by a simulation model. Experimental results were then analysed and discussed in the students' projects. Students' contributions were part of their final grade. The results show that students, taking the course of Modelling and Simulation, thought that application of the simulation model contributes to a greater understanding of the problem, the faster finding of solutions, and enhanced confidence of the participants. The results are explained and discussed using a learning model.

scholarly journals Systems Approach to Tourism: A Methodology for Defining Complex Tourism System

Organizacija ◽  
2017 ◽  
Vol 50 (3) ◽  
pp. 208-215 ◽  
Author(s):  
Tadeja Jere Jakulin
Keyword(s):  
Complex System ◽  
System Dynamics ◽  
Simulation Model ◽  
Systems Approach ◽  
Strategic Decision ◽  
Market Area ◽  
Causal Loop Diagram ◽  
Systems Methodology ◽  
Loop Diagram ◽  
Causal Loop

Abstract Background and Purpose: The complexity of the tourism system, as well as modelling in a frame of system dynamics, will be discussed in this paper. The phaenomenon of tourism, which possesses the typical properties of global and local organisations, will be presented as an open complex system with all its elements, and an optimal methodology to explain the relations among them. The approach we want to present is due to its transparency an excellent tool for searching systems solutions and serves also as a strategic decision-making assessment. We will present systems complexity and develop three models of a complex tourism system: the first one will present tourism as an open complex system with its elements, which operate inside of a tourism market area. The elements of this system present subsystems, which relations and interdependencies will be explained with two models: causal-loop diagram and a simulation model in frame of systems dynamics. Design/methodology/approach: Systems methodology will be shown as the appropriate one, when we discuss complex systems challenges. For illustration, systems approach and systems methodology will be applied to tourism models. With building a qualitative causal-loop diagram we will describe the tourism system complexity in forms of system’s elements relations. Mutual influences among the elements will be presented with positive and negative loops, which forms circles of reinforcement and balance. This will help us to discuss the problem categorically. The final model will follow the causal-loop diagram. This will be a simulation model in a frame of system dynamics as an illustration of the discussed methodology. Results: The methodology offers the solution of effective and holistic promotion of complex tourism system transformation, which has the potential to go beyond the myth of sustainable tourism and create significant shifts in the approach and acting of the participants (elements of the system) involved. Systems approach brings to tourism and the society, in general, broader dimensions of thinking, the awareness interdependency, interconnectivity, and responsibility for the behaviour of a system, which can be observed by feedback loops. Conclusions: Findings about meaningfulness of systems thinking presented in the paper, are rarely presented to tourism society systemically and with the aim of designing sustainable complex tourism system. They show new approach, systems awareness and teaches thinking “out of the box”. Consequently, the sustainable behaviour is achieved: tourism supply and demand meet on responsible base and they connect to responsible stakeholders.

FUNCTIONAL APPROXIMATION IN MULTISCALE COMPLEX SYSTEMS

2003 ◽  
Vol 06 (02) ◽  
pp. 177-204 ◽  
Author(s):  
ENRICO CAPOBIANCO
Keyword(s):  
Complex System ◽  
Complex Systems ◽  
System Dynamics ◽  
Financial Markets ◽  
Building Block ◽  
Optimization Theory ◽  
Efficient Computation ◽  
Functional Approximation ◽  
Greedy Approximation ◽  
Complex System Dynamics

One common approach for exploring, approximating and estimating complex system dynamics refers to models based on elementary or atomic building block components of easier interpretation and efficient computation. We adopt a combination of wavelets, greedy approximation and subspace techniques to investigate complex systems such as speculative financial markets. These systems are endowed with multiscale and non-stationary dynamics that we aim to artificially learn by using functional approximation and optimization theory. We show that volatility dynamics are embedded in a sequence of nested informative scales and thus a multiscale estimation approach is indicated to deal with them.

scholarly journals A Discrete Event Simulation Model for Evaluating the Performances of an M/G/C/C State Dependent Queuing System

PLoS ONE ◽  
2013 ◽  
Vol 8 (4) ◽  
pp. e58402 ◽  
Author(s):  
Ruzelan Khalid ◽  
Mohd Kamal M. Nawawi ◽  
Luthful A. Kawsar ◽  
Noraida A. Ghani ◽  
Anton A. Kamil ◽  
...  
Keyword(s):  
Simulation Model ◽  
Discrete Event Simulation ◽  
Discrete Event ◽  
Queuing System ◽  
Event Simulation ◽  
Discrete Event Simulation Model ◽  
State Dependent

scholarly journals Toward Global Complex Systems Control The Autonomous Intelligence Challenge

2019 ◽  
Vol 2 (1) ◽  
pp. 11
Author(s):  
Michel Cotsaftis
Keyword(s):  
Complex System ◽  
Complex Systems ◽  
System Dynamics ◽  
Classical Trajectory ◽  
Initial Time ◽  
Full Potential ◽  
Trajectory Space ◽  
Classical Systems ◽  
System Parameters ◽  
General Terms

Complex systems are the emerging new scientific frontier with modern technology advance and new parametric domains study in natural systems. An important challenge is, contrary to classical systems studied so far, the great difficulty in predicting their future behaviour from initial time because, by their very structure, interactions strength between system components is shielding completely their specific individual features. Independent of clear existence of strict laws complex systems are obeying like classical systems, it is however possible today to develop methods allowing to handle dynamical properties of such systems and to master their evolution. So the methods should be imperatively adapted to representing system self organization when becoming complex. This rests upon the new paradigm of passing from classical trajectory space to more abstract trajectory manifolds associated to natural system invariants characterizing complex system dynamics. The methods are basically of qualitative nature, independent of system state space dimension and, because of its generic impreciseness, privileging robustness to compensate for not well known system parameters and functional variations. This points toward the importance of control approach for complex system study in adequate function spaces, the more as for industrial applications there is now evidence that transforming a complicated man made system into a complex one is extremely beneficial for overall performance improvement. But this last step requires larger intelligence delegation to the system requiring more autonomy for exploiting its full potential. A well defined, meaningful and explicit control law should be set by using equivalence classes within which system dynamics are forced to stay, so that a complex system described in very general terms can behave in a prescribed way for fixed system parameters value. Along the line traced by Nature for living creatures, the delegation is expressed at lower level by a change from regular trajectory space control to task space control following system reassessment into its complex stage imposed by the high level of interactions between system constitutive components. Aspects of this situation with coordinated action on both power and information fluxes are handled in a new and explicit control structure derived from application of Fixed Point Theorem which turns out to better perform than (also explicit) extension of Popov criterion to more general nonlinear monotonically upper bounded potentials bounding system dynamics discussed here. An interesting observation is that when correctly amended as proposed here, complex systems are not as commonly believed a counterexample to reductionism so strongly influential in Science with Cartesian method supposedly only valid for complicated systems.

SIMULATION OF A SEA CARGO PORT AS A QUEUING SYSTEM IN ANYLOGIC

2020 ◽  
Vol 4 (26) ◽  
pp. 59-66
Author(s):  
A. G. Morozkov ◽  
◽  
M. R. Yazvenko ◽  
Keyword(s):  
Simulation Model ◽  
Key Words ◽  
Simulation Modeling ◽  
Queue Length ◽  
System Simulation ◽  
Queuing System ◽  
System Model ◽  
System Capacity ◽  
Mathematical Solution ◽  
Structure Simulation

The article presents simplified queuing system model of freight marine port. The article discusses the basic elements of queuing system, its mathematical solution and structure. Simulation model was created using AnyLogic to analyze an effect of system capacity on queue length. The results were analyzed and the solution for queue optimization was proposed. Key words: queuing system, simulation modeling, AnyLogic, marine port, servers, queue.

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