Lagrangian Decomposition, Metaheuristics, and Hybrid Approaches for the Design of the Last Mile in Fiber Optic Networks

Leitner, Markus; Raidl, Günther R.

doi:10.1007/978-3-540-88439-2_12

Cited by 12 publications

(9 citation statements)

References 18 publications

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“…Our delay-bounded path replacement operation guarantees that the tree T i+1 is always a delay-bounded and loop free. To present the candidate paths chosen in the path replacement, we define superpath (based on [11], also called key-path in the literature [33,34]) as the longest simple path in the tree T i , where all internal nodes, except the two end nodes of the path, are relay nodes and each relay node connects exactly two edges. The pseudo-code of VNDMR is presented in Fig.1.…”

Section: Neighborhood Structures Within the Vnd Algorithmsmentioning

confidence: 99%

A Variable Neighborhood Descent Search Algorithm for Delay-Constrained Least-Cost Multicast Routing

Kendall

2009

Lecture Notes in Computer Science

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Abstract. The rapid evolution of real-time multimedia applications requires Quality of Service (QoS) based multicast routing in underlying computer networks. The constrained Steiner Tree, as the underpinning mathematical structure, is a well-known NP-complete problem. In this paper we investigate a variable neighborhood descent (VND) search, a variant of variable neighborhood search, for the delay-constrained leastcost (DCLC) multicast routing problem. The neighborhood structures designed in the VND approaches are based on the idea of path replacement in trees. They are simple, yet effective operators, enabling a flexible search over the solution space of this complex problem with multiple constraints. A large number of simulations demonstrate that our algorithm is highly efficient in solving the DCLC multicast routing problem in terms of the tree cost and execution time. To our knowledge, this is the first study of VND algorithm on the DCLC multicast routing problem. It outperforms other existing algorithms over a range of problem instances.

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Section: Neighborhood Structures Within the Vnd Algorithmsmentioning

confidence: 99%

A Variable Neighborhood Descent Search Algorithm for Delay-Constrained Least-Cost Multicast Routing

Kendall

2009

Lecture Notes in Computer Science

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“…Ways of integrating information gained in LR into a tabu search algorithm is given in [56] and computational results are presented for an example application to the capacitated warehouse location problem. Other, recent examples of using LR to direct SLS algorithms include a genetic algorithm for the prize collecting Steiner tree problem [59], exploiting Lagrangean decomposition for an evolutionary algorithm for the knapsack constrained maximum spanning tree problem [91], or hybrid approaches to the design of the last mile in fiber optic networks [69].…”

Section: Discussionmentioning

confidence: 99%

Usage of Exact Algorithms to Enhance Stochastic Local Search Algorithms

Dumitrescu

Stützle

2009

Matheuristics

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Exact mathematical programming techniques such as branch-andbound or dynamic programming and stochastic local search techniques have traditionally been seen as being two general but distinct approaches for the effective solution of combinatorial optimization problems, each having particular advantages and disadvantages. In several research efforts true hybrid algorithms, which exploit ideas from both fields, have been proposed. In this chapter we review some of the main ideas of several such combinations and illustrate them with examples from the literature. Our focus here is on algorithms that have the main framework given by the local search and use exact algorithms to solve subproblems.

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“…Two algorithms are experimented on real-world and random instances. The results, obtained from two algorithms, were better than previous work in [2] [3] and [8]. In this paper, we compare these proposed algorithms to the heuristic algorithm called GRASP (Greedy Randomized Adaptive Search Procedure [3]) which is the best in the known heuristic algorithms.…”

Section: Introductionmentioning

confidence: 90%

Heuristic Algorithms for Solving the Survivable Problem in the Design of Last Mile Communication Networks

Nguyen¹,

Huynh²

2012

2012 IEEE RIVF International Conference on Computing &Amp; Communication Technologies, Research, Innovation, and Vision for The

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Given a connected, weighted, undirected graph G = (V, E), a set infrastructure nodes and a set customers C includes two customer types whereby customers C1 require a single connection (type-1) and customers C2 need to be redundantly connected (type-2). Survivable Network Design Problem (SNDP) seeks sub-graph of G with smallest weight in which all customers are connected to infrastructure nodes. This problem is NP-hard and has application in the design of the last mile of the real-world communication networks. This paper proposes two new heuristic algorithms for solving SNDP. Results of computational experiments are reported to show the efficiency of proposed algorithms.

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Lagrangian Decomposition, Metaheuristics, and Hybrid Approaches for the Design of the Last Mile in Fiber Optic Networks

Cited by 12 publications

References 18 publications

A Variable Neighborhood Descent Search Algorithm for Delay-Constrained Least-Cost Multicast Routing

A Variable Neighborhood Descent Search Algorithm for Delay-Constrained Least-Cost Multicast Routing

Usage of Exact Algorithms to Enhance Stochastic Local Search Algorithms

Heuristic Algorithms for Solving the Survivable Problem in the Design of Last Mile Communication Networks

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