subsocial nesting - ορισμός. Τι είναι το subsocial nesting
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Τι (ποιος) είναι subsocial nesting - ορισμός

CLASS OF COMPUTIONAL PACKING OPTIMISATION PROCEDURE
Nesting algorithms

Nesting (computing)         
COMPUTING SCIENCE AND INFORMATICS TERM FOR INFORMATION ORGANIZED IN LAYERS OR WITH OBJECTS WITHIN OBJECTS, FOR EXAMPLE RECURSIVELY
Nesting (computers); Nesting (programming)
In computing science and informatics, nestinghttps://study.com/academy/lesson/nesting-loops-statements-in-c-programming.
Nesting instinct         
  • Bird's nest in grass
  • [[Groundhog]] gathering nesting material for its warm [[burrow]]
  • Tawny Mining Bee (''Andrena fulva'') nest entrance
  • Wood rat (''Neotoma lepida'') nest at [[Joshua Tree National Park]]
INSTINCT OR URGE IN PREGNANT ANIMALS CAUSED BY THE INCREASE OF ESTRADIOL (E2) TO PREPARE A HOME FOR THE UPCOMING NEWBORN(S). IT IS FOUND IN A VARIETY OF ANIMALS SUCH AS BIRDS, FISH, SQUIRRELS, MICE AND PIGS AS WELL AS HUMANS
Nesting behavior
Nesting behavior refers to an instinct or urge in pregnant animals associated with an increase of estradiol (E2) to prepare a home for the upcoming newborn(s). Nest building provides protection against predators and competitors that mean to exploit or kill infants.
Nesting (process)         
  • Image 3: Minimizing waste by mixing different parts
  • Image 2: Improved Nesting with rotated parts
  • Nesting components or plies on sheet metal or composite material
MANUFACTURING METHOD TO AVOID WASTE OF MATERIALS
In manufacturing industry, nesting refers to the process of laying out cutting patterns to minimize the raw material waste. Examples include manufacturing parts from flat raw material such as sheet metal.

Βικιπαίδεια

Nesting algorithm

Nesting algorithms are used to make the most efficient use of material or space by evaluating many different possible combinations via recursion.

  1. Linear (1-dimensional): The simplest of the algorithms illustrated here. For an existing set there is only one position where a new cut can be placed – at the end of the last cut. Validation of a combination involves a simple Stock - Yield - Kerf = Scrap calculation.
  2. Plate (2-dimensional): These algorithms are significantly more complex. For an existing set, there may be as many as eight positions where a new cut may be introduced next to each existing cut, and if the new cut is not perfectly square then different rotations may need to be checked. Validation of a potential combination involves checking for intersections between two-dimensional objects.
  3. Packing (3-dimensional): These algorithms are the most complex illustrated here due to the larger number of possible combinations. Validation of a potential combination involves checking for intersections between three-dimensional objects.