TS performs tabu search optimization

Verify checks the validity of the settings and returns nil if everything is ok

GA Performs optimization. The optimization follows three steps: - for current population calculate fitness - select chromosomes with best fitness valu

SA performs simulated annealing algorithm

ACO performs the ant colony optimization algorithm

Performance is the objective, lower is better

Swap produces a neighbor of x by swapping two values

Verify returns an error if settings verification fails

Verify returns an error, if settings are not valid

Verify checks the validity of the settings and returns nil if everything is ok

binaryWeightedChoice returns n indizes with a probability defined by weights it uses a binary search and is more efficient for n > 1 than weightedChoi

ES performs Evolutionary Strategy algorithm suited for minimizing a real valued function (objective) from a starting point x0 It takes advantage of po

Flip produces a neighbor of state by changing the value of one bit

Gauss returns a new vector with gaussian noise. dev is custom deviation

OnePointPerm cuts a in two pieces and fills the gap with values from b while preserving order. 12345678 + 26371485 -> 1234**** + *6*7**85 -> 12346785

PSO performs particle swarm optimization. Objective is the function to minimize, init initializes a tupe of particle and velocity, settings holds algo

TwoPointPerm takes a slice of a and fills the gaps with values from b while preserving order. 12345678 + 26371485 -> **3456** + 2**71*8* -> 27345618

Verify returns an error if settings verification fails

weightedChoice returns n indizes with a probability defined by weights weightedChoice([0.5, 0.3, 0.2], 3) will return 3 indizes. 0 with probability 0.

Arithmetic chooses u in range and performs c = u * a + (1-u) * b for every element in a and b

Objective is the function to be minimized

TwoPointInt is analogue to OnePointInt with two intersection points

UniformBool uniformly selects attributes from a or b panics if a and b have different lengths

Verify checks validity of the ACOSettings and returns nil if settings are ok

Crossover merges this and another genome to produce a descendant

Fitness returns the objective function value for this genome

Neighbor produces a related state for local search

OnePointBool randomly chooses intersection point. Takes all elements from a, where the index is below the intersection point and b for the rest panics

OnePointInt randomly chooses intersection point. Takes all elements from a, where the index is below the intersection point and b for the rest panics

TwoPointBool is analogue to OnePointBool with two intersection points

resets schedule and writes nurse assignments into the schedule

resets schedule and writes nurse assignments into the schedule

resets schedule and writes nurse assignments into the schedule

resets schedule and writes nurse assignments into the schedule

findInSlice counts appearances of value in slice

DropPheromone leaves pheromone (depending on the performance) on the path of this ant

Equal returns true, when other state is equal to current one

Evaporate is called after one iteration and reduces the amount of pheromone on the paths

Flipn produces a neighbor of state by changing the value of n bits

Init initializes the ant for creating a new tour

Mutate returns a neighbor of this genome

PerceivePheromone returns a pheromone slice where each element represents the pheromone for the next step (encoded by position)

Step performs one step to the next position (encoded by int) and returns true when the tour is finished

SwapClose produces a neighbor of x by swapping two values that are next to each other

assembleTour creates a tour list for the given vehicle index

assembleTour creates a tour list for the given vehicle index

assembleTour creates a tour list for the given vehicle index

knapsack evaluates the objective for a given selection. Adds penalties for exceeding maxWeight

sets all assignments in this schedule to false

sets all assignments in this schedule to false

sets all assignments in this schedule to false

sets all assignments in this schedule to false

schedulePenalty returns a penalty value for schedule properties that we want to avoid. e.g. having two shifts on the same day or working on a day afte

schedulePenalty returns a penalty value for schedule properties that we want to avoid. e.g. having two shifts on the same day or working on a day afte

schedulePenalty returns a penalty value for schedule properties that we want to avoid. e.g. having two shifts on the same day or working on a day afte

schedulePenalty returns a penalty value for schedule properties that we want to avoid. e.g. having two shifts on the same day or working on a day afte

scheduleQuality returns a quality value for respecting shift requests and off requests

scheduleQuality returns a quality value for respecting shift requests and off requests

scheduleQuality returns a quality value for respecting shift requests and off requests

scheduleQuality returns a quality value for respecting shift requests and off requests

shiftInSlice helps checking if two states are equal

swapShift chooses two nurses and swaps a shift between these nurses

swapShift chooses two nurses and swaps a shift between these nurses

transferShift transfers a shift from one nurse to another one

transferShift transfers a shift from one nurse to another one

Crossover uses uniform Crossover for booleans

Crossover returns a child genome which is a combination of the current and other genome. Here an the Arithmetic crossover operation is used

Crossover combines the assignments and the order of both genomes

DropPheromone increases pheromone amount by 0.2 not considering the performance

DropPheromone adds pheromone to pheromone matrix along the tour of this ant the amount of pheromone that is dropped depends on the performance of the