A double evolutionary pool memetic algorithm is proposed to solve the examination timetabling problem. To improve the performance of the proposed algorithm, two evolutionary pools, that is, the main evolutionary pool ...
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A double evolutionary pool memetic algorithm is proposed to solve the examination timetabling problem. To improve the performance of the proposed algorithm, two evolutionary pools, that is, the main evolutionary pool and the secondary evolutionary pool, are employed. The genetic operators have been specially designed to fit the examination timetabling problem. A simplified version of the simulated annealing strategy is designed to speed the convergence of the algorithm. A clonal mechanism is introduced to preserve population diversity. Extensive experiments carried out on 12 benchmark examination timetabling instances show that the proposed algorithm is able to produce promising results for the uncapacitated examination timetabling problem.
Many applications of wireless sensor networks (WSNs) require the tracking and the surveillance of target objects. The information to be gathered about the target may be related to only a particular monitored sub-area....
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Many applications of wireless sensor networks (WSNs) require the tracking and the surveillance of target objects. The information to be gathered about the target may be related to only a particular monitored sub-area. Therefore, it is desirable to direct queries only to the nodes monitoring this particular area and for energy saving reasons, only the queried nodes should respond. In this paper, we introduce two new efficient distributed algorithms for finding the minimum number of connected perimeter sensor nodes that are sufficient to cover the perimeter of queried region, where the union of their sensing regions covers the perimeter of queried area. The simulation results show that our proposed algorithms achieve significant reduction in communication load, while preserving full perimeter coverage. (C) 2011 Elsevier Inc. All rights reserved.
Studies an interactive computerized algorithm for multicriteria vehicle routing problems (VRP). Development of the interactive computerized algorithm; Determination of the most favorable vehicle routes for multicriter...
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Studies an interactive computerized algorithm for multicriteria vehicle routing problems (VRP). Development of the interactive computerized algorithm; Determination of the most favorable vehicle routes for multicriteria VRP.
We study the effect of restart, and retry, on the mean completion time of a generic process. The need to do so arises in various branches of the sciences and we show that it can naturally be addressed by taking advant...
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We study the effect of restart, and retry, on the mean completion time of a generic process. The need to do so arises in various branches of the sciences and we show that it can naturally be addressed by taking advantage of the classical reaction scheme of Michaelis and Menten. Stopping a process in its midst—only to start it all over again—may prolong, leave unchanged, or even shorten the time taken for its completion. Here we are interested in the optimal restart problem, i.e., in finding a restart rate which brings the mean completion time of a process to a minimum. We derive the governing equation for this problem and show that it is exactly solvable in cases of particular interest. We then continue to discover regimes at which solutions to the problem take on universal, details independent forms which further give rise to optimal scaling laws. The formalism we develop, and the results obtained, can be utilized when optimizing stochastic search processes and randomized computer algorithms. An immediate connection with kinetic proofreading is also noted and discussed.
We propose a branch and bound reduced algorithm for quadratic programming problems with quadratic constraints. In this algorithm, we determine the lower bound of the optimal value of original problem by constructing a...
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We propose a branch and bound reduced algorithm for quadratic programming problems with quadratic constraints. In this algorithm, we determine the lower bound of the optimal value of original problem by constructing a linear relaxation programming problem. At the same time, in order to improve the degree of approximation and the convergence rate of acceleration, a rectangular reduction strategy is used in the algorithm. Numerical experiments show that the proposed algorithm is feasible and effective and can solve small-and medium-sized problems.
A new numerical procedure is presented to reconstruct a fixed-free spring-mass system from two auxiliary spectra, which are nondisjoint. The method is amodification of the fast orthogonal reduction algorithm, which is...
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A new numerical procedure is presented to reconstruct a fixed-free spring-mass system from two auxiliary spectra, which are nondisjoint. The method is amodification of the fast orthogonal reduction algorithm, which is less computationally expensive than others in the literature. Numerical results are obtained, showing the accuracy of the algorithm.
In this paper we analyze the limiting behavior of several randomized work stealing algorithms in a dynamic setting. Our models represent the limiting behavior of systems as the number of processors grows to infinity u...
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In this paper we analyze the limiting behavior of several randomized work stealing algorithms in a dynamic setting. Our models represent the limiting behavior of systems as the number of processors grows to infinity using differential equations. The advantages of this approach include the ability to model a large variety of systems and to provide accurate numerical approximations of system behavior even when the number of processors is relatively small. We show how this approach can yield significant intuition about the behavior of work stealing algorithms in realistic settings.
Previous studies on emergency management of large-scale urban networks have commonly concentrated on system development to off-load intensive computations to remote cloud servers or improving communication quality dur...
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Previous studies on emergency management of large-scale urban networks have commonly concentrated on system development to off-load intensive computations to remote cloud servers or improving communication quality during a disaster and ignored the effect of energy consumption of vehicles, which can play a vital role in large-scale evacuation owing to the disruptions in energy supply. Hence, in this paper we propose a cloud-enabled navigation system to direct vehicles to safe areas in the aftermath of a disaster in an energy and time efficient fashion. A G-network model is employed to mimic the behaviors and interactions between individual vehicles and the navigation system, and analyze the effect of re-routing decisions toward the vehicles. A gradient descent optimization algorithm is used to gradually reduce the evacuation time and fuel consumption of vehicles by optimizing the probabilistic choices of linked road segments at each intersection. The re-routing decisions arrive at the intersections periodically and will expire after a short period. When a vehicle reaches an intersection, if the latest re-routing decision has not expired, the vehicle will follow this advice, otherwise, the vehicle will stick to the shortest path to its destination. The experimental results indicate that the proposed algorithm can reduce the evacuation time and the overall fuel utilization especially when the number of evacuated vehicles is large.
The present work aims at proposing an efficient technique for signed binary multiplication using unsigned, multiply instruction. Numerous examples are provided to show efficiency of the proposed approach in the contex...
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The present work aims at proposing an efficient technique for signed binary multiplication using unsigned, multiply instruction. Numerous examples are provided to show efficiency of the proposed approach in the context of practical software implementation. Performance of the technique is compared to the software emulated versions of classical methods, such as radix-2 Booth method, reversal of sign method (negative to positive conversion) and sign extension method. The proposed algorithm is suitable for embedded systems which are based on widespread microprocessors/microcontrollers which have an unsigned multiplication in their instruction set but no signed multiply instruction. The algorithm includes only one unsigned multiplication and two subtractions. Various samples of code presenting the signed multiplication are provided in the assembly language for an MCS-51 compatible microcontroller. The comparison of the performance of algorithm is carried out for classical MCS-51 core and innovative AT89LPx core treated as a reference microcontroller. (C) 2011 Published by Elsevier Ltd.
A new approach regarding real-time low-level image and signal processing is presented. This new approach deals with the philosophy of finding a method for designing and executing algorithms (filters), using the most m...
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A new approach regarding real-time low-level image and signal processing is presented. This new approach deals with the philosophy of finding a method for designing and executing algorithms (filters), using the most minimum possible complexity. The proposed method is based on a special formation of coordinate logic filters (CLFs), the coordinate logic order statistics (CL-OS) filters. CL-OS introduces a minimalistic approach in filter design followed by the greatest possible efficiency in terms of speed, quality, complexity and energy consumption. Moreover CL-OS reveals new signal information;this information gives a different interpretation of the original signal, it could be said that it acts like a function applying a nonlinear quantisation in order to approximate the desired output.
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