Using global and local catastrophes across sub-populations in parallel evolutionary computing
First Claim
1. A method comprising:
- tracking forward progress of a first sub-population across generations thereof, wherein the first sub-population is one of a plurality of sub-populations that form a population of candidate solutions to an optimization problem for which a solution is being searched by a parallel evolutionary computing process;
at a current generation of the first sub-population, determining that forward progress of the first sub-population fails a set of one or more forward progress criteria;
in response to determining that the forward progress of the first sub-population fails the set of one or more forward progress criteria at the current generation, invoking a local catastrophe on the current generation of the first sub-population;
re-populating the first sub-population after the local catastrophe is invoked; and
re-establishing the first sub-population after re-populating while constraining migration to the first sub-population.
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Abstract
A parallel genetic algorithm computing process tracks forward progress of a first sub-population across generations thereof. The first sub-population is one of a plurality of sub-populations that form a population of candidate solutions to an optimization problem. At a current generation of the first sub-population, it is determined that forward progress of the first sub-population fails a set of one or more forward progress criteria. In response to determining that the forward progress of the first sub-population fails the set of one or more forward progress criteria at the current generation, a local catastrophe is invoked on the current generation of the first sub-population. The first sub-population is re-populated after the local catastrophe is invoked. The first sub-population is re-established after re-populating while constraining migration to the first sub-population.
68 Citations
8 Claims
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1. A method comprising:
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tracking forward progress of a first sub-population across generations thereof, wherein the first sub-population is one of a plurality of sub-populations that form a population of candidate solutions to an optimization problem for which a solution is being searched by a parallel evolutionary computing process; at a current generation of the first sub-population, determining that forward progress of the first sub-population fails a set of one or more forward progress criteria; in response to determining that the forward progress of the first sub-population fails the set of one or more forward progress criteria at the current generation, invoking a local catastrophe on the current generation of the first sub-population; re-populating the first sub-population after the local catastrophe is invoked; and re-establishing the first sub-population after re-populating while constraining migration to the first sub-population. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8)
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Specification