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98
Experimental Analysis of Heuristics for the STSP
- Local Search in Combinatorial Optimization
, 2001
"... In this and the following chapter, we consider what approaches one should take when one is confronted with a real-world application of the TSP. What algorithms should be used under which circumstances? We ..."
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Cited by 68 (1 self)
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In this and the following chapter, we consider what approaches one should take when one is confronted with a real-world application of the TSP. What algorithms should be used under which circumstances? We
Salient Closed Boundary Extraction with Ratio Contour
- IEEE Trans. on Pattern Analysis and Machine Intelligence
, 2005
"... We present ratio contour, a novel graph-based method for extracting salient closed boundaries from noisy images. This method operates on a set of boundary fragments that are produced by edge detection. Boundary extraction identifies a subset of these fragments and connects them sequentially to for ..."
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Cited by 61 (16 self)
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We present ratio contour, a novel graph-based method for extracting salient closed boundaries from noisy images. This method operates on a set of boundary fragments that are produced by edge detection. Boundary extraction identifies a subset of these fragments and connects them sequentially to form a closed boundary with the largest saliency. We encode the Gestalt laws of proximity and continuity in a novel boundary-saliency measure based on the relative gap length and average curvature when connecting fragments to form a closed boundary. This new measure attempts to remove a possible bias toward short boundaries. We present a polynomial-time algorithm for finding the most-salient closed boundary. We also present supplementary preprocessing steps that facilitate the application of ratio contour to real images. We compare ratio contour to two closely related methods for extracting closed boundaries: Elder and Zucker's method based on the shortest-path algorithm and Williams and Thornber's method based on spectral analysis and a strongly-connected-components algorithm. This comparison involves both theoretic analysis and experimental evaluation on both synthesized data and real images.
Multilevel Refinement for Combinatorial Optimisation Problems
- SE10 9LS
, 2001
"... Abstract. We consider the multilevel paradigm and its potential to aid the solution of combinatorial optimisation problems. The multilevel paradigm is a simple one, which involves recursive coarsening to create a hierarchy of approximations to the original problem. An initial solution is found (some ..."
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Cited by 57 (5 self)
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Abstract. We consider the multilevel paradigm and its potential to aid the solution of combinatorial optimisation problems. The multilevel paradigm is a simple one, which involves recursive coarsening to create a hierarchy of approximations to the original problem. An initial solution is found (sometimes for the original problem, sometimes the coarsest) and then iteratively refined at each level. As a general solution strategy, the multilevel paradigm has been in use for many years and has been applied to many problem areas (most notably in the form of multigrid techniques). However, with the exception of the graph partitioning problem, multilevel techniques have not been widely applied to combinatorial optimisation problems. In this paper we address the issue of multilevel refinement for such problems and, with the aid of examples and results in graph partitioning, graph colouring and the travelling salesman problem, make a case for its use as a metaheuristic. The results provide compelling evidence that, although the multilevel framework cannot be considered as a panacea for combinatorial problems, it can provide an extremely useful addition to the combinatorial optimisation toolkit. We also give a possible explanation for the underlying process and extract some generic guidelines for its future use on other combinatorial problems.
Sensor Placement in Municipal Water Networks
- J. Water
, 2003
"... We present a mixed-integer programming (MIP) formulation for sensor placement optimization in municipal water distribution systems that includes the temporal char-acteristics of contamination events and their impacts. Typical network water quality simulations track contaminant concentration and move ..."
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Cited by 51 (12 self)
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We present a mixed-integer programming (MIP) formulation for sensor placement optimization in municipal water distribution systems that includes the temporal char-acteristics of contamination events and their impacts. Typical network water quality simulations track contaminant concentration and movement over time, computing con-taminant concentration time-series for each junction. Given this information, we can compute the impact of a contamination event over time and determine affected loca-tions. This process quantifies the benefits of sensing contamination at different junc-tions in the network. Ours is the first MIP model to base sensor placement decisions on such data, compromising over many individual contamination events. The MIP formulation is mathematically equivalent to the well-known p-median facility location
Analysis and Approximation of Optimal Co-Scheduling on Chip Multiprocessors
, 2008
"... Cache sharing among processors is important for Chip Multiprocessors to reduce inter-thread latency, but also brings cache contention, degrading program performance considerably. Recent studies have shown that job co-scheduling can effectively alleviate the contention, but it remains an open questio ..."
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Cited by 47 (11 self)
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Cache sharing among processors is important for Chip Multiprocessors to reduce inter-thread latency, but also brings cache contention, degrading program performance considerably. Recent studies have shown that job co-scheduling can effectively alleviate the contention, but it remains an open question how to efficiently find optimal co-schedules. Solving the question is critical for determining the potential of a co-scheduling system. This paper presents a theoretical analysis of the complexity of co-scheduling, proving its NPcompleteness. Furthermore, for a special case when there are two sharers per chip, we propose an algorithm that finds the optimal co-schedules in polynomial time. For more complex cases, we design and evaluate a sequence of approximation algorithms, among which, the hierarchical matching algorithm produces near-optimal schedules and shows good scalability. This study facilitates the evaluation of co-scheduling systems, as well as offers some techniques directly usable in proactive job co-scheduling.
Energy-aware secure multicast communication in ad-hoc networks using geographic location information
- IN PROCEEDINGS OF INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP’03
, 2003
"... The problem of securing multicast communications in an energy-constrained ad-hoc network requires the efficient management of cryptographic quantities. We show that existing efficient key distribution techniques for wired networks that rely on logical hierarchies are extremely energy inefficient. We ..."
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Cited by 44 (9 self)
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The problem of securing multicast communications in an energy-constrained ad-hoc network requires the efficient management of cryptographic quantities. We show that existing efficient key distribution techniques for wired networks that rely on logical hierarchies are extremely energy inefficient. We also show that the consideration of the physical location of the members is critical for developing energy-efficient key distribution schemes. By exploiting the spatial correlation between the members of the multicast group, we construct an energy-aware key distribution scheme. We present simulation results to illustrate the improvements achieved by our proposed algorithm.
Dynamic programming approximations for a stochastic inventory routing problem
- Transportation Science
, 2004
"... This work is motivated by the need to solve the inventory routing problem when implementing a business practice called vendor managed inventory replenishment (VMI). With VMI, vendors monitor their customers ’ inventories, and decide when and how much inventory should be replenished at each customer. ..."
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Cited by 29 (3 self)
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This work is motivated by the need to solve the inventory routing problem when implementing a business practice called vendor managed inventory replenishment (VMI). With VMI, vendors monitor their customers ’ inventories, and decide when and how much inventory should be replenished at each customer. The inventory routing problem attempts to coordinate inventory replenishment and transportation in such a way that the cost is minimized over the long run. We formulate a Markov decision process model of the stochastic inventory routing problem, and propose approximation methods to find good solutions with reasonable computational effort. We indicate how the proposed approach can be used for other Markov decision processes involving the control of multiple resources. ∗ Supported by the National Science Foundation under grant DMI-9875400.
A Linear Time Approximation Algorithm for Weighted Matchings in Graphs
, 2003
"... Approximation algorithms have so far mainly been studied for problems that are not known to have polynomial time algorithms for solving them exactly. Here we propose an approximation algorithm for the weighted matching problem in graphs which can be solved in polynomial time. The weighted matching p ..."
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Cited by 25 (3 self)
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Approximation algorithms have so far mainly been studied for problems that are not known to have polynomial time algorithms for solving them exactly. Here we propose an approximation algorithm for the weighted matching problem in graphs which can be solved in polynomial time. The weighted matching problem is to find a matching in an edge weighted graph that has maximum weight. The first polynomial time algorithm for this problem was given by Edmonds in 1965. The fastest known algorithm for the weighted matching problem has a running time of O(nm+n 2 log n). Many real world problems require graphs of such large size that this running time is too costly. Therefore there is considerable need for faster approximation algorithms for the weighted matching problem. We present a linear time approximation algorithm for the weighted matching problem with a performance ratio arbitrarily close to 2/3
Efficient Exact Inference in Planar Ising Models
"... We give polynomial-time algorithms for the exact computation of lowest-energy states, worst margin violators, partition functions, and marginals in certain binary undirected graphical models. Our approach provides an interesting alternative to the well-known graph cut paradigm in that it does not im ..."
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Cited by 24 (0 self)
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We give polynomial-time algorithms for the exact computation of lowest-energy states, worst margin violators, partition functions, and marginals in certain binary undirected graphical models. Our approach provides an interesting alternative to the well-known graph cut paradigm in that it does not impose any submodularity constraints; instead we require planarity to establish a correspondence with perfect matchings in an expanded dual graph. Maximum-margin parameter estimation for a boundary detection task shows our approach to be efficient and effective. 1
