rapidhouse.algorithm package¶

Submodules¶

class rapidhouse.algorithm.alg.Algorithm(ranges)[source]¶

Bases: object

This class is abstracting that algorithm for searching the solution of a combination.

get_group()[source]¶

Getter for the group of solution.

Returns:	the group of solution.

init_group(idb, basic)[source]¶

Initialize a group of solution.

Parameters:	idb – Instance of informationdb.InformationDb. basic (tuple) – the basic[0] is list of the basic groups. the basic[1] is the group length.

mutate_gauss(lst, sigma)[source]¶

Mutate with a normal random number.

Parameters:	lst (list) – a list. sigma (int) – Standard deviation.
Return type:	list
Returns:	the mutated list.

random_indexes(lst)[source]¶

Return list of random indexes.

class rapidhouse.algorithm.ga.GaSuneko(ranges, mutprob=0.3, elite=0.2, ranran=0.3)[source]¶

This class is using GA as that algorithm for searching the solution of a combination.

Parameters:	ranges (list) – Pass to the parent class. mutprob (float) – the mutation probability. elite (float) – the percentage of surviving a elite. step (float) – the amount of change for the mutation.

crossover(pop1, pop2)[source]¶

Crossover the populations.

Parameters:	pop1 (list) – a population. pop2 (list) – a population.
Return type:	list
Returns:	the crossedover population.

mutate(pop)[source]¶

Mutate the population.

next(scores)[source]¶

Generate the population of the next generation.

Parameters:	scores (tuple) – set of the population and the cost of the population.

undx(parent1, parent2, parent3)[source]¶

Parameters:	parent1 (list) – a population. parent2 (list) – a population. parent3 (list) – a population.
Return type:	list
Returns:	the reproduced population.