Department for Operations Research in Traffic
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Research fields
Techniques of operations research in transport
Most problems in traffic engineering, transportation is relatively easy to formulate words. In the analysis and formulation of the problem, engineers often in the next step verbal description of the problem are transformed into the corresponding mathematical description. The main components of mathematical description of the problem variables, constraints and criteria function. Constraints can be physical or financial.Physical limitations resulting from various engineering regulations, recommendations, performance means of transport, urban conditions, or characteristics of the traffic terminals. Financial constraints are mainly caused by the budget available, or certain financial regulations. Values of certain variables may be permissible or impermissible. Values of variables are permissible in cases where they met all the prescribed limits. Criteria function that reflects the goals of the decision maker wants to achieve. So, for example, the criteria function often reflects the tendency to maximize revenue or profit, or desire to minimize costs. To solve traffic problems, kriterijumnska function very often points to the tendency of analysts to maximize the quality of transport services offered.
Mathematical description of the real problem that is solved is called a mathematical model of the considered problem. Under the algorithm is understood quantitative method that uses an analyst for the purpose of solving the mathematical model. Algorithms are described by a set of instructions that a user of the algorithm needs to perform one after the other. By finding the optimal solution involves finding the permissible values of variables that lead to the optimal value of criterion function.
To solve the problem of traffic transportation engineering techniques are used Linear Programming, Integer programming, dynamic programming, multiple criteria programming, as well as various heuristics and algorithms Metaheuristički.
Techniques of soft Account (Soft Computing) in a traffic inženjerstrvu
Planning, design and management of transportation systems (especially intelligent transportation systems (ITS)) are extremely complex tasks.Whole range of traffic and transport parameters is characterized by uncertainty, subjectivity, imprecision and ambiguity. Every day, dispatchers, drivers, air traffic controllers, operators, passengers, engineers and planners use subjective knowledge, approximately known values and / or linguistic information when making decisions. Complex traffic and transportation problems can successfully be solved, first of all, using different intelligent systems which are based on knowledge and techniques from different scientific disciplines.
These intelligent systems will need to be able to recognize different situations and to make appropriate decisions without explicitly determined relationship between the individual variables that characterize the transport system. A new generation of intelligent systems that are used for transport planning and management of various traffic and transport processes need to be able to perform generalization, to adapt and learn based on new knowledge and new information. Modern intelligent systems are based on computer techniques able to count the words(Fuzzy Logic), to learn and adapt (Artificial neurionske network) and to perform in a systematic way of stochastic search and optimization(genetic algorithms). The set of techniques known as m ECU account (Soft Computing).
Techniques of soft accounts can be used to solve a wide variety of traffic and transport problems (traffic control at isolated intersections and along corridors, management of pouring ramps on the highway, keeping vehicles on the network, the problems of route selection, making the distribution of traffic on the network design schedules and routes traffic sredststava, dispatching transport equipment). It is especially important to use this technique for solving problems characterized by uncertainty (randomness, fuzziness, ...) and dependent on time (dynamic problems, problems to be solved in real time).
The Association of European Operational Research Societies (EURO)
www.euro-online.org
The Institute for Operations Research and the Management Sciences (INFORMS)
www.informs.org
Serbian Library Consortium for Coordinated Acquisition
www.kobson.nb.rs
Most problems in traffic engineering, transportation is relatively easy to formulate words. In the analysis and formulation of the problem, engineers often in the next step verbal description of the problem are transformed into the corresponding mathematical description. The main components of mathematical description of the problem variables, constraints and criteria function. Constraints can be physical or financial.Physical limitations resulting from various engineering regulations, recommendations, performance means of transport, urban conditions, or characteristics of the traffic terminals. Financial constraints are mainly caused by the budget available, or certain financial regulations. Values of certain variables may be permissible or impermissible. Values of variables are permissible in cases where they met all the prescribed limits. Criteria function that reflects the goals of the decision maker wants to achieve. So, for example, the criteria function often reflects the tendency to maximize revenue or profit, or desire to minimize costs. To solve traffic problems, kriterijumnska function very often points to the tendency of analysts to maximize the quality of transport services offered.
Mathematical description of the real problem that is solved is called a mathematical model of the considered problem. Under the algorithm is understood quantitative method that uses an analyst for the purpose of solving the mathematical model. Algorithms are described by a set of instructions that a user of the algorithm needs to perform one after the other. By finding the optimal solution involves finding the permissible values of variables that lead to the optimal value of criterion function.
To solve the problem of traffic transportation engineering techniques are used Linear Programming, Integer programming, dynamic programming, multiple criteria programming, as well as various heuristics and algorithms Metaheuristički.
Techniques of soft Account (Soft Computing) in a traffic inženjerstrvu
Planning, design and management of transportation systems (especially intelligent transportation systems (ITS)) are extremely complex tasks.Whole range of traffic and transport parameters is characterized by uncertainty, subjectivity, imprecision and ambiguity. Every day, dispatchers, drivers, air traffic controllers, operators, passengers, engineers and planners use subjective knowledge, approximately known values and / or linguistic information when making decisions. Complex traffic and transportation problems can successfully be solved, first of all, using different intelligent systems which are based on knowledge and techniques from different scientific disciplines.
These intelligent systems will need to be able to recognize different situations and to make appropriate decisions without explicitly determined relationship between the individual variables that characterize the transport system. A new generation of intelligent systems that are used for transport planning and management of various traffic and transport processes need to be able to perform generalization, to adapt and learn based on new knowledge and new information. Modern intelligent systems are based on computer techniques able to count the words(Fuzzy Logic), to learn and adapt (Artificial neurionske network) and to perform in a systematic way of stochastic search and optimization(genetic algorithms). The set of techniques known as m ECU account (Soft Computing).
Techniques of soft accounts can be used to solve a wide variety of traffic and transport problems (traffic control at isolated intersections and along corridors, management of pouring ramps on the highway, keeping vehicles on the network, the problems of route selection, making the distribution of traffic on the network design schedules and routes traffic sredststava, dispatching transport equipment). It is especially important to use this technique for solving problems characterized by uncertainty (randomness, fuzziness, ...) and dependent on time (dynamic problems, problems to be solved in real time).
Areas of research
- Design of transport networks
- Flow control in transport networks
- Development of models for managing traffic demand
- Development of models for management of traffic congestion
- Development of algorithms for solving the problem of traffic routing and dispatch of resources
- Mathematical modeling of the crew planning problem
- Management of disturbances in traffic and transport
- Fuzzy logic systems in traffic
- Artificial neural network traffic
- Evolutionary computing traffic
- Intelligence Group in traffic
- Location analysis of traffic
- Performance measurement of traffic and transport system
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Important links
The Association of European Operational Research Societies (EURO)
www.euro-online.org
The Institute for Operations Research and the Management Sciences (INFORMS)
www.informs.org
Serbian Library Consortium for Coordinated Acquisition
www.kobson.nb.rs