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Variable neighborhood search for the bounded diameter minimum spanning tree problem
 Proceedings of the 18th Mini Euro Conference on Variable Neighborhood Search
, 2005
"... The bounded diameter minimum spanning tree problem is an NPhard combinatorial optimization problem with applications in various fields like communication network design. We propose a general variable neighborhood search approach for it, utilizing four different types of neighborhoods. They were d ..."
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Cited by 14 (9 self)
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The bounded diameter minimum spanning tree problem is an NPhard combinatorial optimization problem with applications in various fields like communication network design. We propose a general variable neighborhood search approach for it, utilizing four different types of neighborhoods. They were designed in a way enabling an efficient incremental evaluation and search for the best neighboring solution. An experimental comparison on instances with complete graphs with up to 1000 nodes indicates that this approach consistently outperforms the so far leading evolutionary algorithms with respect to solution quality and computation time.
A new 0–1 ILP approach for the bounded diameter minimum spanning tree problem
 Proceedings of the 2nd International Network Optimization Conference
, 2005
"... The bounded diameter minimum spanning tree (BDMST) problem is NPhard and appears e.g. in communication network design when considering certain quality of service requirements. Prior exact approaches for the BDMST problem mostly rely on network flowbased mixed integer linear programming and Miller ..."
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Cited by 13 (7 self)
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The bounded diameter minimum spanning tree (BDMST) problem is NPhard and appears e.g. in communication network design when considering certain quality of service requirements. Prior exact approaches for the BDMST problem mostly rely on network flowbased mixed integer linear programming and MillerTuckerZemlinbased formulations. This article presents a new, compact 0–1 integer linear programming model, which is further strengthened by dynamically adding violated connection and cycle elimination constraints within a branchandcut environment. The proposed approach is empirically compared to two recently published formulations. It turns out to work well in particular on dense instances with tight diameter bounds.
Computing A DiameterConstrained Minimum Spanning Tree
, 2001
"... In numerous practical applications, it is necessary to find the smallest possible tree with a bounded diameter. A diameterconstrained minimum spanning tree (DCMST) of a given undirected, edgeweighted graph, G, is the smallestweight spanning tree of all spanning trees of G which contain no path wi ..."
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Cited by 8 (0 self)
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In numerous practical applications, it is necessary to find the smallest possible tree with a bounded diameter. A diameterconstrained minimum spanning tree (DCMST) of a given undirected, edgeweighted graph, G, is the smallestweight spanning tree of all spanning trees of G which contain no path with more than k edges, where k is a given positive integer. The problem of finding a DCMST is NPcomplete for all values of k; 4 k (n  2), except when all edgeweights are identical. A DCMST is essential for the efficiency of various distributed mutual exclusion algorithms, where it can minimize the number of messages communicated among processors per critical section. It is also useful in linear lightwave networks, where it can minimize interference in the network by limiting the traffic in the network lines. Another practical application requiring a DCMST arises in data compression, where some algorithms compress a file utilizing a tree datastructure, and decompress a path in the tree to access a record. A DCMST helps such algorithms to be fast without sacrificing a lot of storage space. We present a survey of the literature on the DCMST problem, study the expected diameter of a random labeled tree, and present five new polynomialtime algorithms for an approximate DCMST. One of our new algorithms constructs an approximate DCMST in a modified greedy fashion, employing a heuristic for selecting an edge to be added to iii the tree in each stage of the construction. Three other new algorithms start with an unconstrained minimum spanning tree, and iteratively refine it into an approximate DCMST. We also present an algorithm designed for the special case when the diameter is required to be no more than 4. Such a diameter4 tree is also used for evaluating the quality of o...
Neighbourhood Searches for the Bounded Diameter . . .
, 2006
"... We consider the Bounded Diameter Minimum Spanning Tree problem and describe four neighbourhood searches for it. They are used as local improvement strategies within a variable neighbourhood search (VNS), an evolutionary algorithm (EA) utilising a new encoding of solutions, and an ant colony optimisa ..."
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Cited by 4 (0 self)
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We consider the Bounded Diameter Minimum Spanning Tree problem and describe four neighbourhood searches for it. They are used as local improvement strategies within a variable neighbourhood search (VNS), an evolutionary algorithm (EA) utilising a new encoding of solutions, and an ant colony optimisation (ACO). We compare the performance in terms of effectiveness between these three hybrid methods on a suite of popular benchmark instances, which contains instances too large to solve by current exact methods. Our results show that the EA and the ACO outperform the VNS on almost all used benchmark instances. Furthermore, the ACO yields most of the time better solutions than the EA in longterm runs, whereas the EA dominates when the computation time is strongly restricted.
Constraint Programming for the Diameter Constrained Minimum Spanning Tree Problem
"... Given an undirected connected graph G = (V,E) with a set V of vertices, a set E of edges, and costs cij associated to every edge [i,j] ∈ E, with i < j, the Diameter Minimum Spanning Tree Problem (DCMST) consists in finding a minimum spanning tree T = (V,E ′), with E ′ ⊆ E, where the diameter ..."
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Cited by 2 (0 self)
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Given an undirected connected graph G = (V,E) with a set V of vertices, a set E of edges, and costs cij associated to every edge [i,j] ∈ E, with i < j, the Diameter Minimum Spanning Tree Problem (DCMST) consists in finding a minimum spanning tree T = (V,E ′), with E ′ ⊆ E, where the diameter
The Economic Addition of Functionality to a Network
 In Proc. of High Performance Computing and Networking
, 1997
"... . In the operation of communication and computer networks, it may become desirable or necessary to add a new function to the network through the placement of the corresponding electronic device within certain existing user locations. This will involve deciding which user locations will have devices ..."
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Cited by 1 (1 self)
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. In the operation of communication and computer networks, it may become desirable or necessary to add a new function to the network through the placement of the corresponding electronic device within certain existing user locations. This will involve deciding which user locations will have devices placed at them as well as deciding an assignment of users to device locations. The objective when adding the new function is to choose these locations and assignments such that the combined cost of placing the devices and routing users to their assigned device locations is minimized. This problem, which we call the device placement problem, is closely related to the simple plant location problem and the pmedian problem. Like these problems, the device placement problem is NPhard, and thus it is highly unlikely that efficient methods for solving this problem to optimality exist. We discuss and test several heuristic methods for the device placement problem, as well as a very efficient meth...
A New Approach for a Restricted Concentrator Location Problem
"... this paper we consider a restricted version of the problem of locating "access facilities", or concentration points, to permit economical connection of users to resources. This problem has been already studied [16]. Actually, we consider only one resource that does not have a important place in the ..."
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this paper we consider a restricted version of the problem of locating "access facilities", or concentration points, to permit economical connection of users to resources. This problem has been already studied [16]. Actually, we consider only one resource that does not have a important place in the optimization problem. This assumption leads to a strong relation with the problem of finding a minimum rrooted 2height spanning tree, giving as result conceptually easy heuristics, that are easilly implemented as well. In the next section we describe in details the restricted concentrator location problem, and some related problems often found in the literature. In section
A New Hybrid Genetic Algorithm for Solving the Bounded Diameter Minimum Spanning Tree Problem
"... Abstract — In this paper, a new hybrid genetic algorithm – known as HGA – is proposed for solving the Bounded Diameter Minimum Spanning Tree (BDMST) problem. We experiment with HGA on two sets of benchmark problem instances, both Euclidean and NonEuclidean. On the Euclidean problem instances, HGA i ..."
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Abstract — In this paper, a new hybrid genetic algorithm – known as HGA – is proposed for solving the Bounded Diameter Minimum Spanning Tree (BDMST) problem. We experiment with HGA on two sets of benchmark problem instances, both Euclidean and NonEuclidean. On the Euclidean problem instances, HGA is shown to outperform the previous best two Genetic Algorithms (GAs) reported in the BDMST literature, while on the NonEuclidean problem instance, HGA performs comparably with these two GAs. T I.
Neighborhood Search for the Bounded Diameter Minimum Spaning Tree
"... Many optimization problems including the network design problem of finding the bounded diameter minimum spanning tree are computationally intractable. Therefore, a practical approach for solving such problems is to employ heuristic algorithms that can find solution close to the optimal one within a ..."
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Many optimization problems including the network design problem of finding the bounded diameter minimum spanning tree are computationally intractable. Therefore, a practical approach for solving such problems is to employ heuristic algorithms that can find solution close to the optimal one within a reasonable amount of time. Neighborhood search algorithms are a wide class of algorithms where at each iteration an improved solution is found by searching the “neighborhood ” of the current solution. A critical issue in the design of a neighborhood search algorithm is the choice of the neighborhood structure. Literature reveals that the larger the neighborhood, the better is the quality of the locally optimal solutions and the greater is the accuracy of the final solution obtained. At the same time, the larger the neighborhood search, the longer it takes to search the neighborhood for optimum. For this reason, an efficient search strategy is required to produce an effective heuristic in large neighborhoods. This paper focus on two known neighborhood structures for the BDMST problem. Both types of neighborhoods are large in the sense that they contain exponentially large number of candidate solutions. A novel intelligent neighborhood search technique (INST) is introduced and compared with the previously published local search techniques. Keywords Bounded Diameter Minimum spanning tree, Local search, Heuristics. I.
Algorithm Designing for Broadcasting in MANET 1
"... There are a lot of advancements going on in radio technologies. With the advent of technologies, we also need to improve our methods for their efficient usage. We face several problems in Broadcasting. The most common of these problems is making efficient BDMSTs to minimize distance between nodes. I ..."
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There are a lot of advancements going on in radio technologies. With the advent of technologies, we also need to improve our methods for their efficient usage. We face several problems in Broadcasting. The most common of these problems is making efficient BDMSTs to minimize distance between nodes. In this paper our focus is on genetic algorithm, which is being considered among the most proficient BDMST algorithms. Genetic algorithm works more efficiently provided its initial population is already processed. Thus, we have taken our initial population from NRGH algorithm. In this paper we have included all our studies and works to make a progressively efficient BDMST. This paper is not for best results but its a combination of enhancements towards better solution.