This paper is concerned with the problem of finding optimal sub-routes from a set of predefined candidate transit routes with the objectives of maximizing transit ridership as well as minimizing operational costs. The...
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This paper is concerned with the problem of finding optimal sub-routes from a set of predefined candidate transit routes with the objectives of maximizing transit ridership as well as minimizing operational costs. The main contributions of this paper are: (1) considering transit ridership maximization in a multi-objective bi-level optimization framework;(2) proposing a greedy algorithm for the multi-objective design problem;(3) applying an efficient path-based algorithm to solve the lower level multi-modal traffic assignment problem. Numerical experiments indicate that the proposed algorithm is not only able to approximate the Pareto-optimal solutions with satisfactory accuracy, but also achieves a fast performance even for problems of real-world scale.
greedy algorithm is a common-used method to solve many different types of problems. Researches were done a lot that use greedy algorithm to solve classical transportation problems. This paper discussed how to apply gr...
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ISBN:
(纸本)9781510842915
greedy algorithm is a common-used method to solve many different types of problems. Researches were done a lot that use greedy algorithm to solve classical transportation problems. This paper discussed how to apply greedy algorithm in transportation problems with warehouses location. The main idea of the improved algorithm is adding average fixed costs to unit transport costs. Then we use this method to solve a realistic problem in a company called Sport ***, and we found that although greedy algorithm usually cannot give out the optimal solution, it could provide a satisfactory suboptimal solution simply and quickly. And when the scale of problem increases, its solution will become closer to the optimal one. However, it still has some other limitations in solving more realistic problems.
This document presents a non-rigid registration algorithm for the use of brain magnetic resonance (MR) images comparison. More precisely, we want to compare pre-operative and post-operative MR images in order to asses...
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This document presents a non-rigid registration algorithm for the use of brain magnetic resonance (MR) images comparison. More precisely, we want to compare pre-operative and post-operative MR images in order to assess the deformation due to a surgical removal. The proposed algorithm has been studied in Chesseboeuf et al. ((Non-rigid registration of magnetic resonance imaging of brain. IEEE, 385-390. doi:ExternalRef RefSource10.1109/IPTA.2015.7367172 RefSource RefTarget Address="10.1109/IPTA.2015.7367172" TargetType="DOI", 2015), following ideas of Trouv, (An infinite dimensional group approach for physics based models in patterns recognition. Technical Report DMI Ecole Normale Sup,rieure, Cachan, 1995), in which the author introduces the algorithm within a very general framework. Here we recalled this theory from a practical point of view. The emphasis is on illustrations and description of the numerical procedure. Our version of the algorithm is associated with a particular matching criterion. Then, a section is devoted to the description of this object. In the last section we focus on the construction of a statistical method of evaluation.
We study greedy approximation in uniformly smooth Banach spaces. The Weak Chebyshev greedy algorithm (WCGA), introduced and studied in [6], is defined for any Banach space X and a dictionary D, and provides nonlinear ...
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We study greedy approximation in uniformly smooth Banach spaces. The Weak Chebyshev greedy algorithm (WCGA), introduced and studied in [6], is defined for any Banach space X and a dictionary D, and provides nonlinear n-term approximation with respect to D. In this paper we study the Approximate Weak Chebyshev greedy algorithm (AWCGA) a modification of the WCGA, that was studied in [7]. In the AWCGA we are allowed to calculate n-term approximation with a perturbation in computing the norming functional and a relative error in calculating the approximant. Such permission is natural for the numerical applications and simplifies realization of the algorithm. We obtain conditions that are necessary and sufficient for the convergence of the AWCGA for any element of X. In particular, we show that if perturbations and errors are from 4 space then the conditions for the convergence of the AWCGA are the same as for the WCGA. For specifically chosen perturbations and errors we estimate the rate of convergence for any element f from the closure of the convex hull of D and demonstrate that in special cases the AWCGA performs as well as the WCGA. (C) 2015 Elsevier Inc. All rights reserved.
Nowadays,there is an increasingly hot topic among the academia which concerns the exiquisite place that algorthm produce.A superior algorithm can not only soup up one thing,but also maximize the benefits and generate ...
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Nowadays,there is an increasingly hot topic among the academia which concerns the exiquisite place that algorthm produce.A superior algorithm can not only soup up one thing,but also maximize the benefits and generate the smallest *** kinds of algorithms abounds,such as dynamic programming method,greedy algorithm and backtracking *** is shown in this paper,the issue of customer service priorities,to make arrangements for the priority of service,allow all customers to wait for the shortest *** solutions to this problem overflow,first come first service,the shortest service first,for *** all these don't very well in meeting the real *** the greedy algorithms,the response radio as the primary consideration to solve the problem,is a very simple but effective results of the method.
Software maintainability is the ease with which a software system can be modified to correct faults, improve performance or other attributes of the source code. Bad smells are symptoms of deeper problem that indicates...
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ISBN:
(纸本)9781509020287
Software maintainability is the ease with which a software system can be modified to correct faults, improve performance or other attributes of the source code. Bad smells are symptoms of deeper problem that indicates the need for refactoring which is the process of changing internal structure of the software without affecting its external attributes. Applying different refactoring techniques in different parts of a code results in changed maintainability value every time. Therefore, sequence in which refactoring should be applied is important so that optimal results can be obtained. In this study, we have proposed an approach for evaluating sequence of refactoring by with the help of greedy algorithm. The algorithm selects locally optimal solution at each stage with the hope of finding global optimal solution. Different sequences are generated and applied to the source code to calculate sum of software maintainability values. greedy algorithm helps in finding the optimal sequence out of all the search space. We have evaluated the approach with source code having god class, long method, feature envy, long parameter list, data clumps, data class, class hierarchy problem, empty catch block, exception thrown in finally block and nested try statement bad smells which are detected manually. Hence our approach is able to identify sequence for refactoring as well as best refactoring which will increase maintainability and enhance software quality.
Applications of the Incremental algorithm, which was developed in the theory of greedy algorithms in Banach spaces, to approximation and numerical integration are discussed. In particular, it is shown that the Increme...
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ISBN:
(纸本)9783319335070;9783319335056
Applications of the Incremental algorithm, which was developed in the theory of greedy algorithms in Banach spaces, to approximation and numerical integration are discussed. In particular, it is shown that the Incremental algorithm provides an efficient way for deterministic construction of cubature formulas with equal weights, which give good rate of error decay for a wide variety of function classes.
greedy algorithms are a fundamental class of mathematics and computer science algorithms, defined by their iterative approach of making locally optimal decisions to approximate global optima. In this review, we focus ...
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greedy algorithms are a fundamental class of mathematics and computer science algorithms, defined by their iterative approach of making locally optimal decisions to approximate global optima. In this review, we focus on two greedy algorithms. First, we examine the relaxed greedy algorithm in the context of dictionaries in Hilbert spaces, analyzing the optimality of the definition of this algorithm. Next, we provide a general overview of the thresholding greedy algorithm and the Chebyshev thresholding greedy algorithm, with particular attention to their applications to bases in p-Banach spaces with 0
This paper proposes a new technique of state estimation (SE) for electric power systems. In the proposed scheme, the Phasor Measurement Units (PMU) are first placed optimally using greedy algorithm for cost reduction,...
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ISBN:
(纸本)9781467385879
This paper proposes a new technique of state estimation (SE) for electric power systems. In the proposed scheme, the Phasor Measurement Units (PMU) are first placed optimally using greedy algorithm for cost reduction, while complete observability of system is also obtained. The SE uses a linear measurement model to obtain the estimated states directly, without any iteration, thereby improves the quality of the estimated data base. To reveal the efficacy of the proposed scheme it has been tested on standard IEEE 5-bus, 14-bus, 30-bus, 57-bus and 118-Bus test systems and the test results are presented.
Finding the optimization of power allocation of subcarrier is always a challenge in MIMO-OFDMA schemes in order to maximize the capacity of the system. Resources allocation is process how set of network is decide in w...
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ISBN:
(纸本)9781509011780
Finding the optimization of power allocation of subcarrier is always a challenge in MIMO-OFDMA schemes in order to maximize the capacity of the system. Resources allocation is process how set of network is decide in wireless system. This research is to study restriction of proportional rate and total power among user in MIMO-OFDMA scheme and the power allocation and capacity of subcarrier in the scheme. The objectives are to suggest by using greedy Power Allocation for capacity increment in MIMO-OFDMA system and to evaluate the system by greedy Subcarrier Allocation. Simulation results show that the proposed algorithm can improve the capacity of the network compared with the waterfilling when using signal-to-noise ratio (SNR) with value 6dB. The proposed algorithm shows comparison between the noise to sub-channel ratio and power allocation in the midst of data sub-channel for 25, 75 and 100 users. It shows that there is no significant difference in power allocation of data subcarriers even if the number of users is increased.
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