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Types & classes48 in github.com/LeonSering/rapid_solve

⨍ Functions 144◇ Types & classes 48

EnumBaseValue

src/objective/base_value.rs:18

EnumCoefficient

src/objective/coefficient.rs:13

ClassDistanceIndicator

src/examples/tsp/objective.rs:6

ClassDistanceIndicator

src/examples/tsp/tsp_tour_with_info/objective.rs:7

ClassEvaluatedSolution

src/objective/evaluated_solution.rs:10

ClassFifthIndicator

src/objective/tests.rs:63

ClassFirstIndicator

src/objective/tests.rs:15

ClassFourthIndicator

src/objective/tests.rs:51

InterfaceIndicator

An atomic quality of the solution. E.g., `total_distance` or `number_of_tours`.

src/objective/indicator.rs:5

ClassLinearCombination

A linear combination of [`Indicators`][`Indicator`] (each equipped with an [`Coefficient`]). Forms a level of the [`Objective`][`super::Objective`].

src/objective/linear_combination.rs:8

InterfaceLocalImprover

Determines for a given solution (as [`EvaluatedSolution`]) the best neighbor that has an smaller [`ObjectiveValue`][crate::objective::ObjectiveValue].

src/heuristics/local_search/local_improver/mod.rs:21

ClassLocalSearchSolver

A local search solver that uses a [`Neighborhood`] and an [`Objective`] to find a local minimum. There are a variety of [`LocalImprovers`][`LocalImpro

src/heuristics/local_search/mod.rs:39

ClassMinimizer

[`Minimizer`] searches the whole [`Neighborhood`] of a solution and returns the best neighbor if it is better than the given solution. No parallelism

src/heuristics/local_search/local_improver/minimizer.rs:15

InterfaceNeighborhood

A local search neighborhood that provides for each solution an iterator over all neighbors. The provided `current_solution`, as well as the [`Neighbor

src/heuristics/common/neighborhood.rs:10

ClassObjective

Defines the objective of an optimization problem, which is constant throughout the optimization. Afterwards an objective instance can be used to evalu

src/objective/mod.rs:36

ClassObjectiveValue

src/objective/objective_value.rs:15

InterfaceParallelLocalImprover

Determines for a given solution (as [`EvaluatedSolution`]) the best neighbor that has an smaller [`ObjectiveValue`][crate::objective::ObjectiveValue].

src/heuristics/parallel_local_search/parallel_local_improver/mod.rs:19

ClassParallelLocalSearchSolver

A local search solver that uses a [`ParallelNeighborhood`] and an [`Objective`] to find a local minimum. The `function_between_steps` is executed afte

src/heuristics/parallel_local_search/mod.rs:34

ClassParallelMinimizer

[`ParallelMinimizer`] searches the whole [`ParallelNeighborhood`] of a solution in parallel and returns the best neighbor if it is better than the giv

src/heuristics/parallel_local_search/parallel_local_improver/parallel_minimizer.rs:16

InterfaceParallelNeighborhood

A parallel local search neighborhood that provides for each solution an [`ParallelIterator`] over all neighbors. The provided `current_solution`, as w

src/heuristics/common/neighborhood.rs:23

InterfaceParallelTabuImprover

Determines for a given solution (as [`EvaluatedSolution`]) and a tabu list the best neighbor, that are not tabu, together with new tabus to add to the

src/heuristics/parallel_tabu_search/parallel_tabu_improver/mod.rs:16

ClassParallelTabuMinimizer

[`ParallelTabuMinimizer`] searches the whole [`ParallelTabuNeighborhood`] of a solution (and a tabu list) and returns the best non-tabu neighbor with

src/heuristics/parallel_tabu_search/parallel_tabu_improver/parallel_tabu_minimizer.rs:19

InterfaceParallelTabuNeighborhood

Defines a neighborhood for a tabu search. Compared to a regular neighborhood, a tabu neighborhood takes a tabu list as an additional argument and retu

src/heuristics/parallel_tabu_search/mod.rs:37

ClassParallelTabuSearchSolver

A tabu search solver that uses a [`ParallelTabuNeighborhood`], an [`Objective`], a tabu list size, as well as a termination criterion to find a good s

src/heuristics/parallel_tabu_search/mod.rs:59

ClassParallelThreeOptNeighborhood

Given a [`TspTour`], this [`ParallelNeighborhood`] generates all tours that can be obtained by applying a 3-opt move (deleting three arcs and reconnec

src/examples/tsp/neighborhood.rs:42

ClassParallelThreeOptTabuNeighborhood

A 3-opt [`ParallelTabuNeighborhood`] for the TSP. For a given tour and a tabu list, all 3-opt moves are generated as a [`ParallelIterator`], all moves

src/examples/tsp/solvers/parallel_tabu_search.rs:60

ClassRotatedThreeOptNeighborhood

Given a [`TspTourWithInfo`], this [`Neighborhood`] generates all tours that can be obtained by applying a 3-opt move. It starts with the first index a

src/examples/tsp/tsp_tour_with_info/neighborhood.rs:12

ClassSecondIndicator

src/objective/tests.rs:27

ClassSimulatedAnnealingSolver

A simulated annealing solver that uses a [`Neighborhood`] and an [`Objective`], an `initial_temperature` (`f32` in the magnitute of the objective valu

src/heuristics/simulated_annealing/mod.rs:67

ClassSixthIndicator

src/objective/tests.rs:75

InterfaceSolver

All local-search-based solvers implement this trait.

src/heuristics/mod.rs:13

ClassTabu

src/examples/tsp/solvers/tabu_search.rs:16

ClassTabu

src/examples/tsp/solvers/parallel_tabu_search.rs:18

InterfaceTabuImprover

Determines for a given solution (as [`EvaluatedSolution`]) and a tabu list the best neighbor, that are not tabu, together with new tabus to add to the

src/heuristics/tabu_search/tabu_improver/mod.rs:15

ClassTabuMinimizer

[`TabuMinimizer`] searches the whole [`TabuNeighborhood`] of a solution (and a tabu list) and returns the best non-tabu neighbor with new tabus. No pa

src/heuristics/tabu_search/tabu_improver/tabu_minimizer.rs:18

InterfaceTabuNeighborhood

Defines a neighborhood for a tabu search. Compared to a regular neighborhood, a tabu neighborhood takes a tabu list as an additional argument and retu

src/heuristics/tabu_search/mod.rs:34

ClassTabuSearchSolver

A tabu search solver that uses a [`TabuNeighborhood`], an [`Objective`], a tabu list size, as well as a termination criterion to find a good solution.

src/heuristics/tabu_search/mod.rs:58

ClassTakeAnyRecursion

Searches in parallel for an improving neighbor. The first one that is found by any thread is taken. If no improving neighbor is found, the best soluti

src/heuristics/parallel_local_search/parallel_local_improver/take_any_recursion.rs:28

ClassTakeFirst

Takes the first improving neighbor according to the order of the neighborhood iterator. No parallelism is used. Works for every solution type `S`. Is

src/heuristics/local_search/local_improver/take_first.rs:17

ClassTakeFirstRecursion

Takes the first improving solution according to the neighborhood iterator. If no improvement is found, it takes the best neighbors into recursion. Wor

src/heuristics/local_search/local_improver/take_first_recursion.rs:17

ClassTestSolution

src/objective/tests.rs:6

ClassThirdIndicator

src/objective/tests.rs:39

ClassThreeOptNeighborhood

Given a [`TspTour`], this [`Neighborhood`] generates all tours that can be obtained by applying a 3-opt move (deleting three arcs and reconnecting the

src/examples/tsp/neighborhood.rs:14

ClassThreeOptTabuNeighborhood

A 3-opt [`TabuNeighborhood`] for the TSP. For a given tour and a tabu list, all 3-opt moves are generated, all moves that are tabu (i.e., that would i

src/examples/tsp/solvers/tabu_search.rs:58

ClassThresholdAcceptingSolver

The threshold accepting solver uses a [`Neighborhood`], an [`Objective`], an `initial_threshold` ([`ObjectiveValue`]) and a `threshold_factor` (`f32`

src/heuristics/threshold_accepting/mod.rs:40

ClassTspInstance

A [`TspInstance`] consists of a (potentially asymmetric) distance matrix and can be loading from a [TSPLIB file](http://comopt.ifi.uni-heidelberg.de/s

src/examples/tsp/tsp_instance.rs:15

ClassTspTour

src/examples/tsp/tsp_tour.rs:8

ClassTspTourWithInfo

src/examples/tsp/tsp_tour_with_info/mod.rs:12