Telecommunications network topological design and capacity expansion: Formulations and algorithms

Chang, Suk-Gwon; Gavish, Bezalel

doi:10.1007/bf02136157

Cited by 51 publications

(10 citation statements)

References 13 publications

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“…Some works concentrate on local access networks [5,6,10] while others concentrate on backbone networks [11,12,15,19,32]. Parrish, Cox, Kuehner and Qui [32] address the expansion problem specifically for leased line communication networks, which used two kinds of transmission facilities.…”

Section: Problem Definition and Formulationmentioning

confidence: 99%

“…The aim is then to find a building or an expansion scheme, which minimizes the present worth of total installation and maintenance costs incurred during a given planning horizon. Many authors have pursued this line of research [7,11,12,15,38,39]. Emphasizing the dynamic nature and the intrinsic complexity of the multi-period model, Minoux [29] used a heuristic two-stage decomposition approach to show that the dynamic problem with discontinuous cost functions can be approximated by a static problem with concave cost functions.…”

Section: Problem Definition and Formulationmentioning

confidence: 99%

“…The problem is formulated as a mixed integer problem and a shortest path algorithm is applied to the state transition diagram, in which each node indicates a network state and in which the links between nodes define the corresponding transition between states. Chang and Gavish [11] deal with a different expansion problem in the sense that it incorporates two kinds of fixed costs and a variable cost. The first kind of fixed cost is incurred once when a physical link is installed, while the second is incurred every time a link capacity expansion takes place.…”

Section: Problem Definition and Formulationmentioning

confidence: 99%

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Minimum concave cost multicommodity network design

Bazlamaçcı

Say

2007

Telecommun Syst

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The minimum concave cost multicommodity network design problem (MCMNDP) arises in many application areas, such as transportation planning, energy distribution systems and especially in the design of both packet and circuit switching backbone networks. Exact concave cost optimization algorithms have been developed but they are applicable only if the network size is small. Therefore, MCMNDP is usually solved using non-exact iterative methods. In this paper, such heuristic techniques proposed within the context of circuit switching and packet switching network design are evaluated in detail. Following a comprehensive literature survey, Yaged's linearization, Minoux's greedy and Minoux's accelerated greedy methods have been selected for the circuit switching network design case for further investigation. Minoux's greedy methods are found to create routes that include cycles causing degradation in the quality of the solution; therefore, we propose a simple but effective modification scheme as a cycle elimination strategy. Similarly, but within the context of packet switching network design, Gerla and Kleinrock's concave branch elimination, Gersht's greedy, and Stacey's concave link elimination methods have been selected for further investigation. All of these methods consider aggregate flows on each link, simultaneously re-routing more than one commodity in one step. In this paper, we propose an alternative disaggregate approach, where only one commodity is handled at a time. Our final proposal is the adaptation of the algorithms proposed for circuit switching network design to the packet switching case. Then an extensive comparative computational study is performed for a number of networks and cost structures to help establish the best method with respect to time and solution quality. Our computational results have shown that the performances of the MCMNDP algorithms heavily depend on the network type and the cost structure. The results have also revealed that our proposed modification to Minoux greedy to eliminate cycles leads to considerable improvements and our proposed disaggregate approach gives the best result in some networks with certain cost structures.

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Section: Problem Definition and Formulationmentioning

confidence: 99%

Section: Problem Definition and Formulationmentioning

confidence: 99%

Section: Problem Definition and Formulationmentioning

confidence: 99%

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Minimum concave cost multicommodity network design

Bazlamaçcı

Say

2007

Telecommun Syst

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“…Also, other techniques are used as simulated annealing [33,34], tabu search [35], evolutionary algorithms [36,37,38], ant colony optimization [39] and heuristics [40,32]. For earlier studies about the backbone network design, the reader can refer to [41,32,42,43,44,45,46].…”

Section: Backbone Network Design Problemmentioning

confidence: 99%

Fiber optical network design problems: A case for Turkey

Yazar

Arslan

Karaşan

et al. 2016

Omega

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“…Constraints (12) state that the flow of interval l may not exceed the capacity. The next two sets of constraints, (13) and (14), ensure that the capacity of a certain interval can be utilized only if the capacities of all the lower intervals are installed. In addition, (15) states that the flow of a commodity can be positive on an arc only if there is any capacity available.…”

Section: Multicommodity Flow Constraintsmentioning

confidence: 99%

Optimization of Internet Protocol network design and routing

Holmberg

Yuan²

2003

Networks

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We consider network design and routing for Internet Protocol (IP) traffic. The design problem concerns capacity dimensioning of communication links, where the design cost consists of fixed charges and linear capacity expansion costs. The optimization problem also concerns determining the amount of traffic demand to be carried by the network and the metric used by a shortest path routing protocol. We present a novel linear mixedinteger mathematical formulation and two heuristic solution procedures. The first heuristic uses mixed-integer programming to generate a sequence of routing solutions. The second solution approach is a simulated annealing meta heuristic. Computational experiments for synthesized and real-life networks show that high-quality solutions can be obtained by both approaches.

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Telecommunications network topological design and capacity expansion: Formulations and algorithms

Cited by 51 publications

References 13 publications

Minimum concave cost multicommodity network design

Minimum concave cost multicommodity network design

Fiber optical network design problems: A case for Turkey

Optimization of Internet Protocol network design and routing

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