All Classes and Interfaces

Class
Description
Absolute value constraint
Abstract class the most of the constraints should extend.
 
An instance of the aircraft landing problem
A solution to an aircraft landing instance.
A plane in the problem
 
Arc Consistent AllDifferent Constraint Algorithm described in "A filtering algorithm for constraints of difference in CSPs" J-C.
Forward Checking filtering AllDifferent Constraint Whenever one variable is fixed, this value is removed from the domain of other variables.
 
Boolean variable, that can be used as a 0-1 IntVar
 
 
Factory for search procedures.
Hamiltonian Circuit Constraint with a successor model
 
 
Interface implemented by every Constraint
 
StateManager that will store the state of every created elements at each Copier.saveState() call.
Implementation of State with copy strategy
Implementation of StateInt with copy strategy
Implementation of StateMap with copy strategy
 
 
A solution to an CostProfitTSP instance
Cumulative constraint with time-table filtering
Cumulative constraint with sum decomposition (very slow).
Depth First Search Branch and Bound implementation
 
 
A solution.
Disjunctive Scheduling Constraint: Any two pairs of activities cannot overlap in time.
Constraint enforcing that two activities cannot overlap in time The implementation of this constraint uses reified constraints.
Domain listeners are passed as argument to the IntDomain modifier methods.
 
An EBRP instance, with its distance matrix and time windows EBRP.TimeWindow
A solution.
A time window, represented by the earliest visit time and latest visit time
Element Constraint modeling array[y] = z
Element Constraint modeling array[y] = z
 
Element Constraint modeling matrix[x][y] = z
 
The Eternity II puzzle is an edge-matching puzzle which involves placing 256 square puzzle pieces into a 16 by 16 grid, constrained by the requirement to match adjacent edges.
 
Factory to create Solver, IntVar, Constraint and some modeling utility methods.
Algorithms and Graph interface
Directed graph API
 
 
Interface for integer domain implementation.
 
 
Implementation of a variable with a SparseSetDomain.
A view on a variable of type a*x
A view on a variable of type x+o
A view on a variable of type -x
 
Reified equality constraint
Reified less or equal constraint.
Reified is less or equal constraint b <=> x <= y.
Reified logical or constraint
The JobShop Problem.
 
Less or equal constraint between two variables
Branching combinator that ensures that that the alternatives created are always within the discrepancy limit.
The Magic Series problem.
The Magic Series problem.
The Magic Square problem.
Maximum Constraint
Compute and Maintain a Maximum Matching in the variable-value graph
 
 
 
 
Minimization objective function
Not Equal constraint between two variables
 
The N-Queens problem.
The N-Queens problem.
The N-Queens problem.
Objective object to be used in the DFSearch.optimize(Objective) for implementing the branch and bound depth first search.
 
Logical or constraint x1 or x2 or ... xn
The void function with no argument does not exist in java.util.function, therefore this interface is used in minicp.
Representation of a cumulated Profile data structure as a contiguous sequence of Profile.Rectangle built from a set of Profile.Rectangle using a sweep-line algorithm.
The Quadratic Assignment problem.
The Quadratic Assignment problem.
The Quadratic Assignment problem.
Resource Constrained Project Scheduling Problem.
A constraint problem with no associated objective
Statistics collected during the execution of DFSearch.solve() and DFSearch.optimize(Objective)
Sequential Search combinator that linearly considers a list of branching generator.
The Send-More-Money problem.
 
Implementation of a domain with a sparse-set
Stable Matching problem: Given n students and n companies, where each student (resp.
Object that wraps a reference and can be saved and restored through the StateManager.saveState() / StateManager.restoreState() methods.
A StateEntry is aimed to be stored by a StateManager to revert some state
Object that wraps an integer value that can be saved and restored through the StateManager.saveState() / StateManager.restoreState() methods.
Implementation of an interval that can saved and restored through the StateManager.saveState() / StateManager.restoreState() methods.
A sparse-set that lazily switch from an dense interval representation to a sparse-set representation when a hole is created in the interval.
The StateManager exposes all the mechanisms and data-structures needed to implement a depth-first-search with reversible states.
A generic map that can revert its state with StateManager.saveState() / StateManager.restoreState() methods.
Class to represent a bit-set that can be saved and restored through the StateManager.saveState() / StateManager.restoreState()
Set implemented using a sparse-set data structure that can be saved and restored through the StateManager.saveState() / StateManager.restoreState() methods.
Generic Stack that can be saved and restored through the StateManager.saveState() / StateManager.restoreState() methods.
Steel is produced by casting molten iron into slabs.
Exception that is thrown to stop the execution of DFSearch.solve(), DFSearch.optimize(Objective)
Object that can be saved by the Copier.
Sum Constraint
Implementation of Compact Table algorithm described in
 
Data Structure described in Global Constraints in Scheduling, 2008 Petr Vilim, PhD thesis See The thesis.
Implementation of State with trail strategy
StateManager that will lazily store the state of state object at each Trailer.saveState() call.
Implementation of StateInt with trail strategy
Implementation of StateMap with trail strategy
 
Traveling salesman problem.
Traveling salesman problem.