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The systolic array genetic algorithm, an example of systolic arrays as a reconfigurable design methodology

The systolic array genetic algorithm, an example of systolic...

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IEEE Symposium on FPGAs for Custom Computing Machines

作者： I.M. Bland G.M. Megson Parallel Emergent and Distributed Architectures Laboratory Parallel Emergent and Distributed Architectures Laboratory University of Reading Reading UK University of Reading Reading Berkshire GB

We have designed and constructed a genetic algorithm engine using a systolic design methodology. The approach has a number of advantages. Firstly the design processes is systematic. A C source code version of the algorithm is used as a starting point and progressively the code is re-written into a form from where systolic cells can be designed. Secondly the modular nature of the arrays allow easy expansion of the design for different requirements (larger populations in this example). Hardware designs are re-used extensively and, in combination with reconfigurable computing techniques, can be swapped in or out on an application specific basis to construct arrays of the correct size. This can also be extended to swapping in and out whole elements of the macro-pipeline so that alternative operators, such as Tournament Selection can be employed. Thirdly, a traditional benefit of systolic arrays applies. The resultant design is massively parallel and significant throughput can be achieved.

关键词： Systolic arrays Genetic algorithms Algorithm design and analysis Field programmable gate arrays Computer architecture Costs Process design Very large scale integration Design methodology Laboratories

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Investigating multiploidy's niche 3rd

Investigating multiploidy's niche

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3rd Workshop on Artificial Intelligence and Simulation of Behaviour, AISB 1996

作者： Corne, David Collingwood, Emma Ross, Peter Parallel Emergent and Distributed Architectures Laboratory Department of Computer Science University of Reading RG6 6AY Reading United Kingdom Department of Artificial Intelligence University of Edinburgh EH1 1HN Edinburgh United Kingdom

ISBN: (纸本)3540617493

A multiploid genotype comprises a number of chromosomes, and a 'dominance' mechanism underlying its interpretation. The simplest dominance mechanism uses a 'mask' chromosome, genes in which determine which gene from which chromosome is expressed at each locus. Previous work using contrived test problems showed that a multiploid was sometimes better than a normal genetic algorithm (GA), and sometimes not. Multiploidy seemed particularly helpful in cases where a normal GA would be likely to irretrievably lose important genetic material. Here we continute this investigation in the context of more realistic problems: the multiple knapsack problem, and the set covering problem. There are many complex effects, but experiments tend overall to reinforce the above suggestion. © Springer-Verlag Berlin Heidelberg 1996.

关键词： Genetic algorithms

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Peckish initialisation strategies for evolutionary timetabling 1st

Peckish initialisation strategies for evolutionary timetabli...

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1st International Conference on Practice and Theory of Automated Timetabling, PATAT 1995

作者： Corne, David Ross, Peter Parallel Emergent and Distributed Architectures Laboratory Department of Computer Science University of Reading ReadingRG6 6AY United Kingdom Department of Artificial Intelligence University of Edinburgh 80 South Bridge EdinburghEH1 1HN United Kingdom

ISBN: (纸本)3540617949

Some evolutionary algorithm (EA)/timetabling researchers find benefit from combining an EA with graph-colouring based greedy algorithms, while others opt for a simpler but faster method. We consider a combination of the two approaches, largely retaining the speed of the simpler method while adopting the greedy method to bootstrap the process. In this combination, the initial population is produced by a 'peckish' timetable construction algorithm, similar to a greedy algorithm, but less concerned with finding a best timeslot for an event at each step. We find peckish population initialisation more effective than either greedy or random initialisation on non-trivial problems. Peckish initialisation is shown to aid a simple hill-climbing approach in a simflax way. Finally, we add to the growing observation that hill-climbing often outperforms an EA on timetabling problems, but that this effect is reversed on problems of particular over constrainedness or difficulty. © Springer-Verlag Berlin Heidelberg 1996.

关键词： Evolutionary algorithms

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A genetic algorithm for job-shop problems with various schedule quality criteria 3rd

A genetic algorithm for job-shop problems with various sched...

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3rd Workshop on Artificial Intelligence and Simulation of Behaviour, AISB 1996

作者： Fang, Hsiao-Lan Corne, David Ross, Peter China Steel Corporation Taiwan Parallel Emergent and Distributed Architectures Laboratory Department of Computer Science University of Reading RG6 6AY Reading United Kingdom Department of Artificial Intelligence University of Edinburgh EH1 1HN Edinburgh United Kingdom

ISBN: (纸本)3540617493

Much recent research has investigated the use of genetic algorithms (GAs) in job-shop scheduling. Mostly, this has involved comparison or construction of ingenious reprsentations and operators in the context of finding a schedule which minimises makespan. Many more criteria exist with which to judge schedule quality, however. Often, makespan may be a low priority aspect of schedule quality, We describe a generallyapplicable GA approach to job-shop problems and examine its performance on a range of benchmark problems, for each of a wide range of different schedule quality criteria. Performance is compared against a range of standard heuristic rules, and also against a stochastic hillclimbing (SH) method. We find that the GA does best overall across all kinds of schedule quality criterion. © Springer-Verlag Berlin Heidelberg 1996.

关键词： Genetic algorithms

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The phase-transition niche for evolutionary algorithms in timetabling 1st

The phase-transition niche for evolutionary algorithms in ti...

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1st International Conference on Practice and Theory of Automated Timetabling, PATAT 1995

作者： Ross, Peter Corne, David Terashima-Marm, Hugo Department of Artificial Intelligence University of Edinburgh 80 South Bridge EdinburghEHl 1HN United Kingdom Parallel Emergent k Distributed Architectures Laboratory Department of Computer Science University of Reading ReadingRG6 6AY United Kingdom Centre for Artificial Intelligence ITESM Monterrey Mexico

ISBN: (纸本)3540617949

Constraint satisfaction problems tend to display phase transitions with respect to the effort required by specific problem solving strategies. So far, little is known concerning the causes of phase transitions, or the relative differences between performance of different algorithms around them, especially with respect to stochastic iterative methods such as evolutionary search. Also, work so far on phase transitions concentrates on homogeneous random problems, rather than problems displaying elements of structure typical of more realistic problems. We investigate some of these issues, and uncover some new phase transition regions on timetabling style problems, occurring in the context of varying degrees of problem homogenity as well as (the more standard) graph connectivity. Further, we find that a simple evolutionary algorithm outperforms a simple Stochastic Hillclimber in regions strongly associated with certain phase transitions, and not others. Finally, we discuss various clues to the underlying causes of these phase transitions. © Springer-Verlag Berlin Heidelberg 1996.

关键词： Evolutionary algorithms

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Obtaining multiple distinct solutions with genetic algorithm niching methods 4th

Obtaining multiple distinct solutions with genetic algorithm...

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International Conference on Evolutionary Computation - 4th International Conference on parallel Problem Solving from Nature, PPSN 1996

作者： Turner, Alasdair Corne, David Ritchie, Graeme Ross, Peter Department of Computer Science University College London Gower Street LondonWC1E 6BT United Kingdom Parallel Emergent and Distributed Architectures Laboratory Department of Computer Science University of Reading Whiteknights ReadingRG6 2AY United Kingdom Department of Artificial Intelligence University of Edinburgh 80 South Bridge EdinEH1 1HN United Kingdom

ISBN: (纸本)354061723X

This paper proposes a new technique for improving the number of usefully distinct solutions produced by a Genetic Algorithm (GA) when applied to multimodal problems. The tribes method builds on the spatial selection methods proposed by Collins and Jefferson [1]. We compare the technique with two well-known niching methods (crowding and sharing), spatial selection alone, and a simple control GA method, in the domain of simple timetabling problems. We demonstrate that the tribes technique can greatly improve the efficiency with which a GA can obtain multiple distinct solutions to a problem. © 1996, Springer-Verlag. All rights reserved.

关键词： Genetic algorithms

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