This work presents a class of scaling functions for genetic algorithms. These functions imply individual performance to be expressed as a set of costs. Two basic functions are obtained. Both are based in exponential f...
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This work presents a class of scaling functions for genetic algorithms. These functions imply individual performance to be expressed as a set of costs. Two basic functions are obtained. Both are based in exponential functions and contain a selectivity parameter assuring an adjustable degree of discernment between individuals. The first is translation invariant while the second is both translation and scale invariant. Three examples were used to compare these scaling functions with linear scaling: an integer linear programming problem; a best path finding problem; and a best path finding problem with deceiving characteristics. In all examples, exponential based functions achieved better results than linear scaling.
The demand for mobile telephone service is increasing rapidly. A new formulation for the channel assignment problem (CAP) is proposed. The CAP has been formulated as an integer linear programming problem including com...
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The demand for mobile telephone service is increasing rapidly. A new formulation for the channel assignment problem (CAP) is proposed. The CAP has been formulated as an integer linear programming problem including compatibility and requirement constraints. For the solution of the resulting formulation conventional branch and bound methods have been used. The exploitation of the problem's special structure can improve the computational efficiency of the algorithm used. The algorithm has been applied to different benchmark problems that have appeared in the literature. The presented examples illustrate that using the proposed formulation and a specially designed branch and bound algorithm is possible to solve optimally and efficiently fairly large channel assignment problems.
The underlying design method for massively parallel processor arrays allows one to exploit parallelism in a broader range, because the I/O variables are not considered during the design process of a full-size array. A...
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The underlying design method for massively parallel processor arrays allows one to exploit parallelism in a broader range, because the I/O variables are not considered during the design process of a full-size array. As a consequence of this approach, a reallocation of the I/O ports of the I/O variables at the boundary processors of the processor array is necessary. Algorithms are described for the reallocation of the I/O ports at the array boundaries, leading to a minimal additional latency and taking systolic constraints into account. integer linear programming is used to solve the optimization problems that arise.
This paper reviews the UNIK project which unifies the artificial intelligence (AI) with optimization models for decision support. Our goal is to unify the specification of problems to encompass as many hybrid type of ...
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ISBN:
(纸本)0780332806
This paper reviews the UNIK project which unifies the artificial intelligence (AI) with optimization models for decision support. Our goal is to unify the specification of problems to encompass as many hybrid type of problems as possible from both AI and optimization. Currently, the type of problems selected from the AI side are the rules, compatibility constraints, and neural networks, while linearprogramming and integerprogramming models from the optimization side. The key issue to be resolved for the unification is the unified representation of optimization model and rules so that they can understand each other. The second issue is designing the unified architecture and devising the solution method. This paper reviews the above issues one by one with illustrative applications.
We propose a method of optimal morphological decomposition. We first formulate this kind of problem into a set of linear constraints, and then find out the solution to the set of linear constraints by using an integer...
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ISBN:
(纸本)0780332598
We propose a method of optimal morphological decomposition. We first formulate this kind of problem into a set of linear constraints, and then find out the solution to the set of linear constraints by using an integer linear programming technique. Our method has the following three advantages: (1) the size of the factors can be any n/spl times/n (n/spl ges/3), (2) it can be applied to both convex and concave simply-connected images; (3) optimality is selective and flexible.
A DMA controller that operates in the cycle-stealing mode transfers data by "stealing" bus cycles from an executing program. This cycle stealing operation retards the progress of the executing program and ex...
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A DMA controller that operates in the cycle-stealing mode transfers data by "stealing" bus cycles from an executing program. This cycle stealing operation retards the progress of the executing program and extends its execution time. We first present a method that bounds the worst-case execution time of a program executing concurrently with a cycle-stealing DMA I/O operation in the simple case where the execution time of each machine instruction is fixed. We next extend this method to deal with the case of instruction-cache architectures. We demonstrate the effectiveness of our methods by the results of simulations of several programs.
We present a randomized procedure for rounding fractional perfect matchings to (integral) matchings. If the original fractional matching satisfies any linear inequality, then with high probability, the new matching sa...
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We present a randomized procedure for rounding fractional perfect matchings to (integral) matchings. If the original fractional matching satisfies any linear inequality, then with high probability, the new matching satisfies that linear inequality in an approximate sense. This extends the well-known LP rounding procedure of Raghavan and Thompson (1987), which is usually used to round fractional solutions of linear programs. It also solves an open problem of Luby and Nisan (1993) ("Design an NC procedure for converting near-optimum fractional matchings to near-optimum matchings.") We use the rounding procedure to design n/sup 0(logn//spl epsiv/(2)/) time algorithms for the following: (i) an additive approximation to the 0-1 Quadratic Assignment problem (QAP); (ii) a (1+E)-approximation for "dense" instances of many well-known NP-hard problems, including (an optimization formulation of) GRAPH-ISOMORPHISM, MIN-CUT-linear-ARRANGEMENT, MAX-ACYCLIC-SUBGRAPH, MIN-linear-ARRANGEMENT, and BETWEENNESS. (A "dense" graph is one in which the number of edges is /spl Omega/(n/sup 2/); denseness for the other problems is defined in an analogous way).
A general purpose storage structure called dual-stack, which is practically implementable, is explored for data path synthesis. Dual-stack is an extension of the conventional single-stack. Dual-stacks maintain an effe...
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A general purpose storage structure called dual-stack, which is practically implementable, is explored for data path synthesis. Dual-stack is an extension of the conventional single-stack. Dual-stacks maintain an effective access separation among variables whose lifetime intervals overlap which is not possible in single-stacks. Utilizing this structure can lead to a better performance in the final implementation of the algorithm. The problem of allocating variables to stacks and interconnection allocation has been modeled as a 0-1 integer linear programming (ILP) formulation with the objective to design a data path with a minimum number of stacks, registers and interconnects. The effectiveness of the proposed storage structure is demonstrated with the elliptical wave filter benchmark example.
We present an approximation scheme for strip-packing, or packing rectangles into a rectangle of fixed width and minimum height, a classical NP-hard cutting-stock problem. The algorithm finds a packing of n rectangles ...
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We present an approximation scheme for strip-packing, or packing rectangles into a rectangle of fixed width and minimum height, a classical NP-hard cutting-stock problem. The algorithm finds a packing of n rectangles whose total height is within a factor of (1+/spl epsiv/) of optimal, and has running time polynomial both in n and in 1//spl epsiv/. It is based on a reduction to fractional bin-packing, and can be performed by 5 stages of guillotine cuts.
This paper presents a novel software pipelining approach, which is called Swing Modulo Scheduling (SMS). It generates schedules that are near optimal in terms of initiation interval, register requirements and stage co...
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This paper presents a novel software pipelining approach, which is called Swing Modulo Scheduling (SMS). It generates schedules that are near optimal in terms of initiation interval, register requirements and stage count. Swing Modulo Scheduling is an heuristic approach that has a low computational cost. The paper describes the technique and evaluates it for the Perfect Club benchmark suite. SMS is compared with other heuristic methods showing that it outperforms them in terms of the quality of the obtained schedules and compilation time. SMS is also compared with an integer linear programming approach that generates optimum schedules but with a huge computational cost, which makes it feasible only for very small loops. For a set of small loops, SMS obtained the optimum initiation interval in all the cases and its schedules required only 5% more registers and a 1% higher stage count than the optimum.
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