A problem of interest in network design is that of finding, in a given weighted graph, a minimum-weight spanning tree whose vertices satisfy specified degree restrictions. We present a branch and cut solution procedur...
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A problem of interest in network design is that of finding, in a given weighted graph, a minimum-weight spanning tree whose vertices satisfy specified degree restrictions. We present a branch and cut solution procedure for this NP-complete problem. Our algorithm is implemented and extensively tested. Computational results on 3150 random table problems ranging from 100 to 800 vertices are presented and discussed. (C) 2001 John Wiley & Sons, Inc.
Large time-constrained applications are highly computer-intensive and are often implemented as a complex organization of pipelined data parallel tasks on a pool of embedded processors, DSP processors, and FPGAs. The l...
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Large time-constrained applications are highly computer-intensive and are often implemented as a complex organization of pipelined data parallel tasks on a pool of embedded processors, DSP processors, and FPGAs. The large number of design alternatives available at each task level, the application as a whole, and the special needs of the reconfigurable devices (such as the FPGA) make the manual synthesis of such systems very tedious. The automatic synthesis algorithm in this paper combines exact (MILP-based) and heuristic techniques to solve this problem, which basically involves (1) propagation of timing constraints;(2) pipelining the loops to meet throughput requirements;(3) resource selection and allocation, keeping the processing requirements and the timing constraints in view;(4) scheduling the resources across the tasks to ensure maximum utilization;and (5) hiding the reconfiguration delays of the FPGAs. While the use of MILP techniques helps in getting high-quality results, combining them with heuristics ensures acceptable synthesis times, striking a good balance between quality of results and synthesis time. Our experimental evaluation of the algorithm shows an average 40% in resource cost reduction (compared to manual synthesis) with synthesis times from minutes to as low as a few seconds in some cases.
Combinatorial optimization problems arising in network applications are usually computationally difficult. Typically, one needs to solve a large mixed integer linear programming problem. Over the past decade, the meth...
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Combinatorial optimization problems arising in network applications are usually computationally difficult. Typically, one needs to solve a large mixed integer linear programming problem. Over the past decade, the method of branch and cut has emerged as a powerful technique for solving such problems. In this paper, we focus on computationally difficult network optimization for problems, highlighting the effectiveness of branch and cut methods. (C) 2001 Elsevier Science Ltd. All rights reserved.
The main objective of this paper is to develop an integrated approach to coordinate short-term scheduling of multi-product blending facilities with nonlinear recipe optimization. The proposed strategy is based on a hi...
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The main objective of this paper is to develop an integrated approach to coordinate short-term scheduling of multi-product blending facilities with nonlinear recipe optimization. The proposed strategy is based on a hierarchical concept consisting of three business levels: Long-range planning, short-term scheduling and process control. Long-range planning is accomplished by solving a large-scale nonlinear recipe optimization problem (multi-blend problem). Resulting blending recipes and production volumes are provided as goals for the scheduling level. The scheduling problem is formulated as a mixed-integerlinear program derived from a resource-task network representation. The scheduling model permits recipe changeovers in order to utilize an additional degree of freedom for optimization. By interpreting the solution of the scheduling problem, new constraints can be imposed on the previous multi-blend problem. Thus bottlenecks arising during scheduling are considered already on the topmost long-range planning level. Based on the outlined approach a commercial software system has been designed to optimize the operation of in-line blending and batch blending processes. The application of the strategy and software is demonstrated by a detailed case study. (C) 2001 Elsevier Science Ltd. All rights reserved.
An enhanced 0-1 mixed integer linear programming formulation is proposed for the traffic signal optimization problem based on the cell transmission model. The formulation has several new features that are unavailable ...
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An enhanced 0-1 mixed integer linear programming formulation is proposed for the traffic signal optimization problem based on the cell transmission model. The formulation has several new features that are unavailable in other existing models. The formulation handles physical queues, the number of stops, fixed or dynamic cycle length and splits, and lost time. The unintended vehicle holding problem, common in many existing analytical models, is eliminated in the proposed formulation. The formulation can be used for developing strategies for adaptive traffic control systems. Since the formulation is exact, it can also be used as a benchmark for examining the convergence behavior of existing heuristic algorithms based on the genetic algorithm, fuzzy logic, neural network or other approaches. The formulation can be solved using standard mathematical programming optimizers. The number of 0-1 integers used in the formulation is equal to the total number of intersections multiplied by the length of the entire optimization period.
This paper proposes a genetic algorithm (GA) based economic contracting strategy for standing reserve in a typical standing reserve market. The aim of the contracting procedure is to identify the standing reserve tend...
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ISBN:
(纸本)0780366727
This paper proposes a genetic algorithm (GA) based economic contracting strategy for standing reserve in a typical standing reserve market. The aim of the contracting procedure is to identify the standing reserve tenders to be contracted and the correct-contract order among the tender options received and scheduled reserve alternatives, to meet the reserve requirement at the lowest possible cost. The contract ordering is a simple problem when all options are rendering for a fixed period of time, however, it becomes troublesome with the presence of flexible contracts, i.e. with standing reserve only available for a partial service window. The proposed GA contracting strategy aims to address the complexity caused by flexible contracts. The results for a system with 16 fixed and flexible tender options are presented and compared with those of mixed integer linear programming (MILP) methods.
We report the very first fully automatic datapath tile layout flow. We subdivided the placement process into two steps: a global placement step using simulated annealing, and a new detailed placement step based on ext...
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ISBN:
(纸本)0769509932
We report the very first fully automatic datapath tile layout flow. We subdivided the placement process into two steps: a global placement step using simulated annealing, and a new detailed placement step based on extensive modifications we made to the O-tree algorithm. The modifications have enabled the extended O-tree algorithm to handle the rectilinearly shaped transistor chains and gates common in datapath tile layout. We show that datapath tiles can be placed and routed automatically at the transistor level or at the mixed transistor/gate level, achieving results for the very first time that are competitive to those obtained manually by a skilled designer.
Array intensive computations are characterized by processing of large arrays stored in external memory in multiple loops. Synthesizing these computations onto FPGAs involves automatic translation of the behavioral des...
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ISBN:
(纸本)0769508316
Array intensive computations are characterized by processing of large arrays stored in external memory in multiple loops. Synthesizing these computations onto FPGAs involves automatic translation of the behavioral description into state machines controlled by a clock such that the execution time of the program as a whole is the minimum and area requirement does not exceed a predefined limit. The synthesis algorithm also needs to efficiently sequence the array, accesses taking into account memory access requirements such as pipelining. In this paper we present two algorithms each with a specific emphasis to handle this synthesis problem. Our heuristic algorithm generates good solutions in a very short time (less than a second), while our mixed integer linear programming (MILP) based algorithm can generate optimal solution given sufficient time. Both try to minimize execution time and area. Our algorithms not only look at individual loops to exploit parallelism but also consider them together while deciding the clock. The overall execution time is minimized and not just the number of cycles or the cycle time. They also efficiently synthesize memory accesses to fully exploit the memory pipelining. We compare these two algorithms in terms of their relative strengths.
A novel decomposition method for solving large scale mixed integer linear programming (MILP) problems with block angular structure is proposed to conduct operational planning of energy supply systems with storage unit...
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A novel decomposition method for solving large scale mixed integer linear programming (MILP) problems with block angular structure is proposed to conduct operational planning of energy supply systems with storage units rationally and efficiently. The method is composed of solving two types of problems repeatedly: one is a large scale MILP master problem with the values of part of the integer variables fixed from the results of the other;the other is a small scale MILP subproblem with the values of the simplex multipliers obtained from the results of the former. The method is applied to the operational planning of a heat supply system with cold and hot water storage tanks. The validity and effectiveness of the method is evaluated in terms of solution optimality and computation time. As a result, it turns out that the method is superior to the conventional branch and bound method with the depth-first or best-bound search, (C) 2000 Elsevier Science Ltd. All rights reserved.
This study addresses questions related to flood-control operating procedures followed by the U.S. Army Corps of Engineers, Rock Island District. Application is presented of a mixed integer linear programming model for...
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This study addresses questions related to flood-control operating procedures followed by the U.S. Army Corps of Engineers, Rock Island District. Application is presented of a mixed integer linear programming model for a reservoir system analysis of three U.S. Army Corps of Engineers' projects on the Iowa and Des Moines rivers. A strategy for evaluating the value of coordinated reservoir operations is developed. Results of this study suggest that operating Coralville Reservoir, on the Iowa River, for flood control on the Mississippi River does not provide appreciable benefits and, therefore, an operation plan coordinating releases from Coralville Reservoir with the two reservoirs on the Des Moines River may be unnecessary. Damage-minimizing results were obtained by operating the three reservoirs independently for 8 of the 10 largest hood events on record. Also, a review of the operating procedures for the hood of 1993 illustrates how much damage could have been reduced if inflows could be predicted months in advance or if the existing operating rules were more averse to extreme flood events.
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