#### DMCA

## Concurrent Topology and Routing Optimization in

### Citations

672 | SPEA2: Improving the strength pareto evolutionary algorithm for multiobjective optimization
- Zitzler, Laumanns, et al.
- 2002
(Show Context)
Citation Context ... solution. 3. OPTIMIZATION The proposed network layout optimization approach is based on the combination of a Pseudo-Boolean (PB) solver [3] and a modern Multi-Objective Evolutionary Algorithm (MOEA) =-=[17]-=-. A PB solver is based on a backtracking strategy and efficiently solves Integer Linear Programs (ILPs) with an empty objective function and binary variables. The task of a PB solver is to find an x ∈... |

114 | A fast pseudo-Boolean constraint solver
- Chai, Kuehlmann
- 2003
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Citation Context ...r in at least one objective when compared to any other feasible solution. 3. OPTIMIZATION The proposed network layout optimization approach is based on the combination of a Pseudo-Boolean (PB) solver =-=[3]-=- and a modern Multi-Objective Evolutionary Algorithm (MOEA) [17]. A PB solver is based on a backtracking strategy and efficiently solves Integer Linear Programs (ILPs) with an empty objective function... |

50 | Holistic scheduling and analysis of mixed time/event-triggered distributed embedded systems
- Pop, Eles, et al.
- 2002
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Citation Context ... Both objectives have to be minimized. The costs are an abstract value approximated by a linear function. The average worst-case response times are calculated by the non-linear functions presented in =-=[12]-=-. In TC1, the optimization approach has an overall runtime of 825 seconds. Figure 3 shows the results of the optimization compared to the reference network. Costs and response times are considerably o... |

21 | Period optimization for hard real-time distributed automotive systems
- Davare, Zhu, et al.
- 2007
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Citation Context ...are neglected. Common automatization approaches for the integration phase in the automotive area are restricted to the optimization of parameters, like message priorities [16] or period determination =-=[4]-=-. To the best of our knowledge, an automatic integration of automotive networks, i.e, a concurrent optimization of the topology and routing, is still unexplored. Most common strategies for the optimiz... |

17 | A New 0-1 ILP Approach for the Bounded Diameter Minimum Spanning Tree Problem
- Gruber, Raidl
- 2005
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Citation Context ...ogy and routing, is still unexplored. Most common strategies for the optimization of network layouts are based on Integer Linear Programs (ILPs) or Evolutionary Algorithms (EAs). Known ILP approaches =-=[5, 13]-=- as well as the majority of EA approaches [6, 8] are restricted to predefined topologies like, e.g., spanning tree networks or ring layouts and are not applicable on heterogeneous automotive networks.... |

13 | Efficient symbolic multi-objective design space exploration
- Lukasiewycz, Glaß, et al.
- 2008
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Citation Context ...in optimization flow is illustrated in Figure 2. This novel approach known as SAT decoding has been presented in [9]. It is known to be superior to common methods that are based on ILPs or MOEAs only =-=[10]-=-. To utilize this optimization approach, it is necessary to encode the network integration problem into a binary ILP by defining a set of linear constraints. Additionally, an efficient preprocessing a... |

12 | Sat-decoding in evolutionary algorithms for discrete constrained optimization problems
- Lukasiewycz, Glaß, et al.
- 2007
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Citation Context ... problem as an ILP and incorporate a PB solver that performs the search for feasible solutions. The actual optimization is realized by a combined PB and EA optimization approach known as SAT decoding =-=[9]-=-. This methodology combines the benefits of both, EAs and ILPs, and allows an efficient optimization of the network layout of real-world automotive systems. The remainder of this paper is outlined as ... |

11 | A comparison of encodings and algorithms for multiobjective spanning tree problems
- Knowles, Corne
- 2001
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Citation Context ... strategies for the optimization of network layouts are based on Integer Linear Programs (ILPs) or Evolutionary Algorithms (EAs). Known ILP approaches [5, 13] as well as the majority of EA approaches =-=[6, 8]-=- are restricted to predefined topologies like, e.g., spanning tree networks or ring layouts and are not applicable on heterogeneous automotive networks. Additionally, these ILPs are mainly limited to ... |

11 | A directed cycle-based columnand-cut generation method for capacitated survivable network design, Networks 43
- Rajan, Atamtürk
- 2004
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Citation Context ...ogy and routing, is still unexplored. Most common strategies for the optimization of network layouts are based on Integer Linear Programs (ILPs) or Evolutionary Algorithms (EAs). Known ILP approaches =-=[5, 13]-=- as well as the majority of EA approaches [6, 8] are restricted to predefined topologies like, e.g., spanning tree networks or ring layouts and are not applicable on heterogeneous automotive networks.... |

10 |
Dynamic response time optimization for SDF graphs
- Ziegenbein, Uerpmann, et al.
- 2000
(Show Context)
Citation Context ...network since many solutions are neglected. Common automatization approaches for the integration phase in the automotive area are restricted to the optimization of parameters, like message priorities =-=[16]-=- or period determination [4]. To the best of our knowledge, an automatic integration of automotive networks, i.e, a concurrent optimization of the topology and routing, is still unexplored. Most commo... |

8 | Multiobjective network design for realistic traffic models
- Banerjee, Kumar
- 1904
(Show Context)
Citation Context ... limited to relatively small problems and restricted to the optimization of a single linear function. Recently, multi-stage EA approaches that also cover general topology layouts have been researched =-=[1, 7, 15]-=-. Though being a fast heuristic that can handle several also non-linear objectives, EAs tend to fail on constrained discrete optimization problems with only a few feasible solutions. In fact, many rea... |

6 | Multiobjective EA approach for improved quality of solutions for spanning tree problem
- Kumar, Singh, et al.
- 2005
(Show Context)
Citation Context ... strategies for the optimization of network layouts are based on Integer Linear Programs (ILPs) or Evolutionary Algorithms (EAs). Known ILP approaches [5, 13] as well as the majority of EA approaches =-=[6, 8]-=- are restricted to predefined topologies like, e.g., spanning tree networks or ring layouts and are not applicable on heterogeneous automotive networks. Additionally, these ILPs are mainly limited to ... |

4 |
Capacitated network design considering survivability: An evolutionary approach
- Konak, Smith
- 2004
(Show Context)
Citation Context ... limited to relatively small problems and restricted to the optimization of a single linear function. Recently, multi-stage EA approaches that also cover general topology layouts have been researched =-=[1, 7, 15]-=-. Though being a fast heuristic that can handle several also non-linear objectives, EAs tend to fail on constrained discrete optimization problems with only a few feasible solutions. In fact, many rea... |

4 | How OEMs and suppliers can face the network integration challenges
- Richter, Ernst
- 2006
(Show Context)
Citation Context ...are applied to validate a feasible communication and low latencies. This busload constraint is manufacturer dependent and usually defined by a maximal utilization of the buses ranging from 40% to 60% =-=[14]-=-. In the integration phase, one major task of the designer is to determine the topology and routing for a given set of communicating ECUs. The topology of the network is determined by interconnecting ... |

3 |
Multi-Objective Topology Optimization for Networked Embedded Systems
- Streichert, Haubelt, et al.
- 2006
(Show Context)
Citation Context ... limited to relatively small problems and restricted to the optimization of a single linear function. Recently, multi-stage EA approaches that also cover general topology layouts have been researched =-=[1, 7, 15]-=-. Though being a fast heuristic that can handle several also non-linear objectives, EAs tend to fail on constrained discrete optimization problems with only a few feasible solutions. In fact, many rea... |

2 |
Optimization framework for java
- Opt4J
(Show Context)
Citation Context .... For all testcases, the maximal utilization of the buses is set to 40%. All experiments were carried out on an Intel Pentium 4 3.2 GHz machine with 1 GB RAM. The used optimization framework is Opt4J =-=[11]-=-. 4.1 Preprocessing First, the benefit of the proposed preprocessing algorithm from Section 3.2 is studied. For each testcase, the number of decodings performed by the PB solver is 100 such that a mea... |