Applying an evolutionary algorithm to telecommunication network design
This paper deals with the application of evolutionary computation to telecommunication network design. Design of a two-layer network is considered, where the upper-layer (UL) network uses resources of the lower-layer (LL) network. UL links determine demands for the LL and are implemented using LL pa...
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| Veröffentlicht in: | IEEE transactions on evolutionary computation 2001-08, Vol.5 (4), p.309-322 |
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| creator | Arabas, J. Kozdrowski, S. |
| description | This paper deals with the application of evolutionary computation to telecommunication network design. Design of a two-layer network is considered, where the upper-layer (UL) network uses resources of the lower-layer (LL) network. UL links determine demands for the LL and are implemented using LL paths (admissible paths). Within a fixed LL network topology, given the demands and admissible paths, we aim to find the LL link capacities for implementing the UL links, minimizing the cost of the LL. Robust design issues are also taken into consideration, allowing for failure of a certain part of the LL and postulating that, after some re-allocation in the LL, demands are still realized to an assumed extent. An algorithm based on an evolutionary technique is introduced, with problem-specific genetic operators to improve computing efficiency. A theoretical study of properties of the operators is made and several experiments are performed to tune the parameters of the algorithm. Finally, its performance is compared with other design techniques, including integer programming. |
| doi_str_mv | 10.1109/4235.942526 |
| format | Article |
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Design of a two-layer network is considered, where the upper-layer (UL) network uses resources of the lower-layer (LL) network. UL links determine demands for the LL and are implemented using LL paths (admissible paths). Within a fixed LL network topology, given the demands and admissible paths, we aim to find the LL link capacities for implementing the UL links, minimizing the cost of the LL. Robust design issues are also taken into consideration, allowing for failure of a certain part of the LL and postulating that, after some re-allocation in the LL, demands are still realized to an assumed extent. An algorithm based on an evolutionary technique is introduced, with problem-specific genetic operators to improve computing efficiency. A theoretical study of properties of the operators is made and several experiments are performed to tune the parameters of the algorithm. 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Design of a two-layer network is considered, where the upper-layer (UL) network uses resources of the lower-layer (LL) network. UL links determine demands for the LL and are implemented using LL paths (admissible paths). Within a fixed LL network topology, given the demands and admissible paths, we aim to find the LL link capacities for implementing the UL links, minimizing the cost of the LL. Robust design issues are also taken into consideration, allowing for failure of a certain part of the LL and postulating that, after some re-allocation in the LL, demands are still realized to an assumed extent. An algorithm based on an evolutionary technique is introduced, with problem-specific genetic operators to improve computing efficiency. A theoretical study of properties of the operators is made and several experiments are performed to tune the parameters of the algorithm. Finally, its performance is compared with other design techniques, including integer programming.</description><subject>Algorithm design and analysis</subject><subject>Algorithms</subject><subject>Applied sciences</subject><subject>Asynchronous transfer mode</subject><subject>Biological cells</subject><subject>Computer science; control theory; systems</subject><subject>Computer systems and distributed systems. User interface</subject><subject>Costs</subject><subject>Demand</subject><subject>Evolutionary algorithms</subject><subject>Evolutionary computation</subject><subject>Exact sciences and technology</subject><subject>Genetics</subject><subject>Integer programming</subject><subject>Linear programming</subject><subject>Links</subject><subject>Marketing</subject><subject>Networks</subject><subject>Operators</subject><subject>Protection</subject><subject>Robustness</subject><subject>Software</subject><subject>Studies</subject><subject>Telecommunications</subject><subject>Telecommunications and information theory</subject><subject>Teleprocessing networks. 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User interface</topic><topic>Costs</topic><topic>Demand</topic><topic>Evolutionary algorithms</topic><topic>Evolutionary computation</topic><topic>Exact sciences and technology</topic><topic>Genetics</topic><topic>Integer programming</topic><topic>Linear programming</topic><topic>Links</topic><topic>Marketing</topic><topic>Networks</topic><topic>Operators</topic><topic>Protection</topic><topic>Robustness</topic><topic>Software</topic><topic>Studies</topic><topic>Telecommunications</topic><topic>Telecommunications and information theory</topic><topic>Teleprocessing networks. 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Design of a two-layer network is considered, where the upper-layer (UL) network uses resources of the lower-layer (LL) network. UL links determine demands for the LL and are implemented using LL paths (admissible paths). Within a fixed LL network topology, given the demands and admissible paths, we aim to find the LL link capacities for implementing the UL links, minimizing the cost of the LL. Robust design issues are also taken into consideration, allowing for failure of a certain part of the LL and postulating that, after some re-allocation in the LL, demands are still realized to an assumed extent. An algorithm based on an evolutionary technique is introduced, with problem-specific genetic operators to improve computing efficiency. A theoretical study of properties of the operators is made and several experiments are performed to tune the parameters of the algorithm. 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| ispartof | IEEE transactions on evolutionary computation, 2001-08, Vol.5 (4), p.309-322 |
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| subjects | Algorithm design and analysis Algorithms Applied sciences Asynchronous transfer mode Biological cells Computer science control theory systems Computer systems and distributed systems. User interface Costs Demand Evolutionary algorithms Evolutionary computation Exact sciences and technology Genetics Integer programming Linear programming Links Marketing Networks Operators Protection Robustness Software Studies Telecommunications Telecommunications and information theory Teleprocessing networks. Isdn Vectors |
| title | Applying an evolutionary algorithm to telecommunication network design |
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