An examination is made of the problem of scheduling a set of independent tasks on a given number of identical processors. Preemption is allowed, but a communication delay is assumed. Whenever a task is preempted fro...
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An examination is made of the problem of scheduling a set of independent tasks on a given number of identical processors. Preemption is allowed, but a communication delay is assumed. Whenever a task is preempted from one processor to another, there has to be a delay of at least k time units. It is demonstrated that, if k is equal to one, an optimal schedule can be found in polynomial time but if k is greater than or equal to 2, the corresponding decision problem is NP-complete. It is very unlikely that there is a polynomial time algorithm to find an optimal k-delay schedule for the general case. Of course, this does not mean that no such algorithm exists for special cases. However, for the more general situation, suitable heuristics will be required.
When the nodes of a tree are visited in depth-first order there areoccasional jumps from a deeper level of the tree to a higher level. On the set of all full binarytrees with a given number of nodes there is about 1 j...
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When the nodes of a tree are visited in depth-first order there areoccasional jumps from a deeper level of the tree to a higher level. On the set of all full binarytrees with a given number of nodes there is about 1 jump for every 2 internal nodes, and the averagejump distance is about 2 levels. These averages are close to averages for trees that arise inpolynomial real root isolation.
Numerous multiobjective evolutionary algorithms (EAs) have been designed for constrained optimization over the past two decades. The idea behind these algorithms is to transform constrained optimization problems (COPs...
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Numerous multiobjective evolutionary algorithms (EAs) have been designed for constrained optimization over the past two decades. The idea behind these algorithms is to transform constrained optimization problems (COPs) into multiobjective optimization problems without any constraint, and then solve them. In this article, we propose a new multiobjective method for constrained optimization, which works by converting a COP into a problem with helper and equivalent objectives. An equivalent objective means that its optimal solution set is the same as that of the constrained problem but a helper objective does not. Then, this multiobjective optimization problem is decomposed into a group of subproblems using the weighted sum approach. Weights are dynamically adjusted so that each subproblem eventually tends to a problem with an equivalent objective. We theoretically analyze the computational time of the helper and equivalent objective method on a hard problem called "wide gap." In a wide gap problem, an algorithm needs exponential time to cross between two fitness levels (a wide gap). We prove that using helper and equivalent objectives can shorten the time of crossing the wide gap. We conduct a case study for validating our method. An algorithm with helper and equivalent objectives is implemented. The experimental results show that its overall performance is ranked first when compared with other eight state-of-the-art EAs on IEEE CEC2017 benchmarks in constrained optimization.
A new class of algorithms to estimate the cardinality of very large multisets using constant memory and doing only one pass on the data is introduced here. It is based on order statistics rather than on bit patterns i...
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A new class of algorithms to estimate the cardinality of very large multisets using constant memory and doing only one pass on the data is introduced here. It is based on order statistics rather than on bit patterns in binary representations of numbers. Three families of estimators are analyzed. They attain a standard error of 1/root M using M units of storage. which places them in the same class as the best known algorithms so far. The algorithms have a very simple internal loop, which gives them an advantage in terms of processing speed. For instance, a memory of only 12 kB and only few seconds are sufficient to process a multiset with several million elements and to build an estimate with accuracy of order 2 percent. The algorithms are validated both by mathematical analysis and by experimentations on real internet traffic. (C) 2008 Elsevier B.V. All rights reserved.
Image segmentation is very important for various fields. With the development of computer technology, computer technology has become more and more effective for image segmentation, and it is studied on the basis of pa...
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Image segmentation is very important for various fields. With the development of computer technology, computer technology has become more and more effective for image segmentation, and it is studied on the basis of partial differential equations. The curve representation method in plane differential geometry is expounded, with the SegNet-v2 segmentation model analyzed and tested in medical image segmentation. The test results show that the partial differential equation image segmentation algorithm can achieve more accurate segmentation, especially in medical image segmentation, which can achieve good results, and it is worth in practice to further promote.
In August 2002, Agrawal, Kayal and Saxena announced the first deterministic and polynomial-time primality-testing algorithm. For an input n, the Agarwal-Kayal-Saxena (AKS) algorithm runs in time Omicron (log(7.5) n) (...
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In August 2002, Agrawal, Kayal and Saxena announced the first deterministic and polynomial-time primality-testing algorithm. For an input n, the Agarwal-Kayal-Saxena (AKS) algorithm runs in time Omicron (log(7.5) n) (heuristic time Omicron (log(6) n)). Verification takes roughly the same amount of time. On the other hand, the Elliptic Curve Primality Proving algorithm (ECPP) runs in random heuristic time 6 (log6 n) (some variant has heuristic time complexity Omicron(log(4) n)) and generates certificates which can be easily verified. However, it is hard to analyze the provable time complexity of ECPP even for a small portion of primes. More recently, Berrizbeitia gave a variant of the AKS algorithm, in which some primes (of density Omicron(1/log(2) n)) cost much less time to prove than a general prime does. Building on these celebrated results, this paper explores the possibility of designing a randomized primality-proving algorithm based on the AKS algorithm. We first generalize Berrizbeitia's algorithm to one which has higher density (Omega (1/log log n)) of primes whose primality can be proved in time complexity 6(log4 n). For a general prime, one round of ECPP is deployed to reduce its primality proof to the proof of a random easily
The plurality problem is a game between two participants: Paul and Carole. We are given n balls, each of them is colored with one out of c colors. At any step of the game, Paul chooses two balls and asks whether they ...
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The plurality problem is a game between two participants: Paul and Carole. We are given n balls, each of them is colored with one out of c colors. At any step of the game, Paul chooses two balls and asks whether they are of the same color, whereupon Carole answers yes or no. The game ends when Paul either produces a ball a of the plurality color (meaning that the number of balls colored like a exceeds those of the other colors), or when Paul states that there is no plurality. How many questions L, (n) does Paul have to ask in the worst case? For c = 2, the problem is equivalent to the well-known majority problem which has already been solved (Combinatorica 11 (1991) 383-387). In this paper we show that 3 [n/2]-2 <= L-3 (n) <= [5n/3]-2. Moreover, for any c <= n, we show that surprisingly the naive algorithm for the plurality problem is asymptotically optimal. (c) 2005 Elsevier B.V. All rights reserved.
We present a new approach for solving the All-Pairs Shortest-Path (APSP) problem for planar graphs that exploits the massive on-chip parallelism available in today's Graphics Processing Units (GPUs). We describe t...
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We present a new approach for solving the All-Pairs Shortest-Path (APSP) problem for planar graphs that exploits the massive on-chip parallelism available in today's Graphics Processing Units (GPUs). We describe two new algorithms based on our approach. Both algorithms use Floyd-Warshall method, have near optimal complexity in terms of the total number of operations, while their matrix-based structure is regular enough to allow for efficient parallel implementation on the GPUs. By applying a divide-and-conquer approach, we are able to make use of multi-node GPU clusters, resulting in more than an order of magnitude speedup over fastest known Dijkstra-based GPU implementation and a two-fold speedup over a parallel Dijkstra-based CPU implementation. (C) 2015 Elsevier Inc. All rights reserved.
A vast number of real world problems are coined by an information release over time and the related need for repetitive decision making over time. Optimization problems arising in this context are called online since ...
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A vast number of real world problems are coined by an information release over time and the related need for repetitive decision making over time. Optimization problems arising in this context are called online since decisions have to be made although not all data is known. Due to technological advances, algorithms may also resort to a limited preview (lookahead) on future events. We first embed the paradigm of online optimization with lookahead into the theory of optimization and develop a concise understanding of lookahead. We further find that the effect of lookahead can be decomposed into an informational and a processual component. Based on analogies to discrete event systems, we then formulate a generic modeling framework for online optimization with lookahead and derive a classification scheme which facilitates a thorough categorization of different lookahead concepts. After an assessment of performance measurement approaches with relevance to practical needs, we conduct a series of computational experiments which illustrate how the general concept of lookahead applies to specific instantiations and how a knowledge pool on lookahead effects in applications can be built up using the general classification scheme. (C) 2015 Elsevier Ltd. All rights reserved.
Network motif algorithms have been a topic of research mainly after the 2002-seminal paper from Milo et al. [1], which provided motifs as a way to uncover the basic building blocks of most networks. Motifs have been m...
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Network motif algorithms have been a topic of research mainly after the 2002-seminal paper from Milo et al. [1], which provided motifs as a way to uncover the basic building blocks of most networks. Motifs have been mainly applied in Bioinformatics, regarding gene regulation networks. Motif detection is based on induced subgraph counting. This paper proposes an algorithm to count subgraphs of size k + 2 based on the set of induced subgraphs of size k. The general technique was applied to detect 3, 4 and 5-sized motifs in directed graphs. Such algorithms have time complexity O(a(G)m), O(m(2)) and O(nm(2)), respectively, where a(G) is the arboricity of G(V, E). The computational experiments in public data sets show that the proposed technique was one order of magnitude faster than Kavosh and FANMOD. When compared to NetMODE, acc-Motif had a slightly improved performance.
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