The equal flow problem

Ali, Agha Iqbal; Kennington, Jeffery L.; Shetty, Bala

doi:10.1016/0377-2217(88)90012-4

Cited by 33 publications

(27 citation statements)

References 5 publications

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“…In practice, our estimates r', v', and w', which are made before solving P( r', v', w ' ) , are not likely to be equal to the optimal r*, v*, and w*. In our algorithm, we judge whether the solution is acceptable according to whether the proportionality constraints (2) and ( 3 ) are almost satisied and whether the objective value c,'x* + cFr* has changed little since the previous estimates of v' and w'; the details are in the next section.…”

Section: Motivation For the Algorithmmentioning

confidence: 98%

A fast algorithm for bounded generalized processing networks

Fuller

Lan

1994

Networks

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A bounded generalized processing network model has the structure of a cost-minimizing generalized network, with additional side constraints that, for flows on some arcs, place upper and lower bounds that are proportional to flows on other arcs. We propose and test a heuristic algorithm that takes advantage of the near-network structure by solving a sequence of generalized network LPs whose data are adjusted in a manner suggested by the solution at previous steps. The algorithm extends an earlier algorithm to achieve better solutions, at the cost of more computing effort. In tests, the algorithm is much faster than is application of the general purpose linear programming code MINOS, and the speed advantage increases with problem size: The algorithm is 27 times faster than MINOS on the largest test problem. The algorithm almost always obtains solutions within 0.05% of the optimum. The proportionality constraints are relaxed in the algorithm, yet the solutions to the test problems satisfy the proportionality constraints to within, at worst, 0.25% of the given proportionality limits. 0 7994 John Wi/ey & Sons, /nc.

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Section: Motivation For the Algorithmmentioning

confidence: 98%

A fast algorithm for bounded generalized processing networks

Fuller

Lan

1994

Networks

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“…The min-cost flow problem with equal integral flow constraints is a difficult problem (NPhard) [2]. To trade off solution quality with runtime, we can use heuristic algorithms, such as the one presented in [3], where the authors used a Lagrangian relaxation technique to speed up the min-cost equal-flow problem.…”

Section: Solving Network Flow Problem With Equal Integral Flow Constrmentioning

confidence: 99%

Behavioral synthesis with activating unused flip-flops for reducing glitch power in FPGA

Hsieh

Cong

Zhang

et al. 2008

2008 Asia and South Pacific Design Automation Conference

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In this paper we discuss optimizing the interconnect power of designs implemented in FPGA platforms. In particular, we reduce the glitch power on interconnects associated with the output of functional units in a design. The idea is to activate unused flip-flops to block the propagation of glitches, which takes advantage of the abundant flip-flops in modern FPGA structures. Since the activation of additional flip-flops may cause data hazard problems, we develop several effective behavioral synthesis techniques to prevent such data hazards. We also study the optimality of our techniques. The experimental results show that on average, our methods lead to a 28% reduction in dynamic power in the Xilinx Virtex-II platform.

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“…Ali, Kennington, and Shetty [3] examined a special case of the integer equal flow problem where each arc set R k has cardinality 2. We refer to this as the paired integer equal flow problem.…”

Section: Introductionmentioning

confidence: 99%