This paper describes the use of parallel multipopulation genetic algorithms (GAs) to meet the dynamic nature of job-shop scheduling. A modified genetic technique is adopted by using a specially formulated genetic oper...
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This paper describes the use of parallel multipopulation genetic algorithms (GAs) to meet the dynamic nature of job-shop scheduling. A modified genetic technique is adopted by using a specially formulated genetic operator to provide an efficient optimisation search. The proposed technique has been successfully implemented using the programming language MATrix LABoratory (MATLAB), providing a powerful tool for job-shop scheduling. Comparisons indicate that the proposed genetic algorithm has successfully improved upon the solution obtained from conventional approaches, particularly in coping with jobshop scheduling.
The forwarding speed of IP routers must grow to accommodate the skyrocketing amount of traffic on the Internet. MPLS, which relies on the high processing power of lower layers, is a solution and it is under developing...
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The forwarding speed of IP routers must grow to accommodate the skyrocketing amount of traffic on the Internet. MPLS, which relies on the high processing power of lower layers, is a solution and it is under developing. On the other hand, a WDM network has been expected as a high-speed network, but it is also called a stupid network because of lacking its traffic granularity In order to bridge between these two layers, an IP over WDM network by a concept of MPLS has been proposed. This network has a potential to effectively use large transmission capacity provided by WDM technology. In this paper, we design IP over WDM networks that reconfigure IP routing and lightpaths each day or month. We formulate a problem that maximizes the network throughput based on integer linear programming. Through numerical examples, we show that the increase of the network throughput in IP over WDM networks is larger than that of IP networks. We also show the area where this method is applicable to the reconfigurable network.
In a realistic register-transfer-level component library, there usually exist several different hardware implementations for one generic function. This gives rise to a large design space of component selection which i...
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In a realistic register-transfer-level component library, there usually exist several different hardware implementations for one generic function. This gives rise to a large design space of component selection which is interleaved with the scheduling of operations. Previous methods ignored the presence of multicomponent selection in the process of lower/upper bound estimation of scheduling, and produced the local lower/upper bounds which would cause the suboptimum designs, Opposite to the previous methods, we compute, in this paper, the lower/upper bounds which consider scheduling and component selection simultaneously. A new problem of multicomponent selection integrated with interval scheduling is studied, We present a very interesting and important result that both the lower bound and upper bound of multicomponent selection are obtained on the most cost-effective components which have the minimum area-delay products. This property leads to that the lower bound and upper bound of multicomponent selection can be calculated efficiently. An integer linear programming model and a surrogate relaxation technique are proposed to derive an optimum surrogate lower bound which has the asymptotic performance ratio less than two for a single type of function. An upper bound with the same asymptotic performance ratio is also obtained which turns out to be the optimum solution value of the traditional unicomponent selection with the most cost-effective components. Both the theoretical analysis and the experimental results show that the performance of our bounds are very promising.
Unate and binate covering problems are a subclass of general integer linear programming problems with which several problems in logic synthesis, such as two-level logic minimization and technology mapping, are formula...
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Unate and binate covering problems are a subclass of general integer linear programming problems with which several problems in logic synthesis, such as two-level logic minimization and technology mapping, are formulated. Previous branch-and-bound methods for solving these problems exactly use lower bounding techniques based on finding maximal independent sets, In this paper, we examine lower bounding techniques based on linearprogramming relaxation (LPR) for the covering problem. We show that a combination of traditional reductions (essentiality and dominance) and incremental computation of LPR-based lower bounds can exactly solve difficult covering problems orders of magnitude faster than traditional methods.
Many applications of fast Fourier transforms (FFT's), such as computer tomography, geophysical signal processing, high-resolution imaging radars, and prediction filters, require high-precision output. An error ana...
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Many applications of fast Fourier transforms (FFT's), such as computer tomography, geophysical signal processing, high-resolution imaging radars, and prediction filters, require high-precision output. An error analysis reveals that the usual method of fixed-point computation of FFT's of vectors of length 2(l) leads to an average loss of l/2 bits of precision. This phenomenon, often referred to as computational noise, causes major problems for arithmetic units with limited precision which are often used for real-time applications, Several researchers have noted that calculation of FFT's with algebraic integers avoids computational noise entirely, see, e,g,, [1], We will combine a new algorithm for approximating complex numbers by cyclotomic integers with Chinese remaindering strategies to give an efficient algorithm to compute b-bit precision FFT's of length L, More precisely, we will approximate complex numbers by cyclotomic integers in Z[e(2 pi i/2 pi)] whose coefficients, when expressed as polynomials in e(2 pi i/2n), are bounded in absolute value by some integer M. For fixed n our algorithm runs in time O(log(M)), and produces an approximation with worst case error of O(1/M2n-2-1). We will prove that this algorithm has optimal worst case error by proving a corresponding lower bound on the worst case error of any approximation algorithm for this task. The main tool for designing the algorithms is the use of the cyclotomic units, a subgroup of finite index in the unit group of the cyclotomic held, First implementations of our algorithms indicate that they are fast enough to be used for the design of low-cost high-speed/high-precision FFT chips.
We present a new exact method to plan frequency assignment for mobile radio systems in a geographical region. Frequencies are to be assigned to 'cells' so that the required service is performed under the parti...
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We present a new exact method to plan frequency assignment for mobile radio systems in a geographical region. Frequencies are to be assigned to 'cells' so that the required service is performed under the particular constraint that the overall noise-signal ratio, related to interference, should not exceed a given level for each cell-frequency pair. This NP-hard problem is formulated as an integerlinear Program and solved by an exact branch-and-cut technique, based on strong cutting planes. We start with very few constraints and use separation procedures to detect the violated constraints. The method and its implementation are tested on a library containing 85 real-world instances provided by CSELT, a major research laboratory operating with TIM (one of the Italian mobile radio system managers). We report the exact solution of instances with up to 203 cells within acceptable computing time. (C) 2000 Elsevier Science B.V. All rights reserved.
Cell suppression is a widely used technique for protecting sensitive information in statistical data presented in tabular form. Previous works on the subject mainly concentrate on two- and three-dimensional tables who...
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Cell suppression is a widely used technique for protecting sensitive information in statistical data presented in tabular form. Previous works on the subject mainly concentrate on two- and three-dimensional tables whose entries are subject to marginal totals. In this article we address the problem of protecting sensitive data in a statistical table whose entries are linked by a generic system of linear constraints. This very general setting covers, among others, k-dimensianal tables with marginals, as well as hierarchical and linked tables. In particular, we address the optimization problem known in the literature as the (complementary or secondary) cell suppression problem, in which the information loss due to suppression must be minimized. We introduce a new integer linear programming model and outline an enumerative algorithm for its exact solution. The algorithm can also be used as a heuristic procedure to find near-optimal solutions. Extensive computational results on a test bed of 1,160 real world and randomly generated instances are presented, showing the effectiveness of the approach. In particular, we were able to solve to proven optimality four-dimensional tables with marginals as well as linked tables. To our knowledge, tables of this kind have never been solved optimally by previous authors.
Block-processing can decrease the time and power required to perform any given computation by simultaneously processing multiple samples of input data. The effectiveness of block-processing can be severely limited, ho...
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Block-processing can decrease the time and power required to perform any given computation by simultaneously processing multiple samples of input data. The effectiveness of block-processing can be severely limited, however, if the delays in the dataflow graph of the computation are placed suboptimally. In this paper we investigate the application of retiming for improving the effectiveness of block-processing in computations. In particular, we consider the k-delay problem: Given a computation dataflow graph and a positive integer k, we wish to compute a retimed computation graph in which the original delays have been relocated so that k data samples can be processed simultaneously and fully regularly. We give an exact integer linear programming formulation for the k-delay problem. We also describe an algorithm that solves the k-delay problem fast in practice by relying on a set of necessary conditions to prune the search space. Experimental results with synthetic and random benchmarks demonstrate the performance improvements achievable by block-processing and the efficiency of our algorithm.
This paper newly proposes a self-healing architecture in all-optical WDM networks based on virtual embedded multiple rings (Virtual Multiple Self Healing Rings : VM-SHR). Focusing upon the network design aspect of the...
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ISBN:
(纸本)081943907X
This paper newly proposes a self-healing architecture in all-optical WDM networks based on virtual embedded multiple rings (Virtual Multiple Self Healing Rings : VM-SHR). Focusing upon the network design aspect of the proposed architecture, this paper describes design methodologies for VM-SHR networks. For two major problems in all-optical WDM network design, that is, the connection routing and wavelength assignment problems, we first established solution models based on mathematical programming formulation, each of which can be solved by common integerprogramming algorithms, respectively. In addition, we also developed an efficient heuristic algorithm for the wavelength assignment problem. Their usefulness and performance are demonstrated through the extensive simulation results.
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