Opt

addEqualityConstraint void addEqualityConstraint(T fc, U fc_data, double tol)
void addEqualityConstraint(T fc): Add equality constraint
addEqualityMConstraint void addEqualityMConstraint(uint m, T fc, U fc_data, V tol)
void addEqualityMConstraint(uint m, T fc, U fc_data)
void addEqualityMConstraint(uint m, T fc): Add multiple equality constraints
addInequalityConstraint void addInequalityConstraint(T fc, U fc_data, double tol): Add inequality constraint
addInequalityConstraint void addInequalityConstraint(T fc): Undocumented in source. Be warned that the author may not have intended to support it.
addInequalityMConstraint void addInequalityMConstraint(uint m, T fc, U fc_data, V tol)
void addInequalityMConstraint(uint m, T fc, U fc_data)
void addInequalityMConstraint(uint m, T fc): Add multiple inequality constraints
addPrecondEqualityConstraint void addPrecondEqualityConstraint(T fc, U pre, V fc_data, double tol): Add pre-conditioned equality constraint
addPrecondEqualityConstraint void addPrecondEqualityConstraint(T fc, U pre): Undocumented in source. Be warned that the author may not have intended to support it.
addPrecondInequalityConstraint void addPrecondInequalityConstraint(T fc, U pre, V fc_data, double tol): Add pre-conditioned inequality constraint.
addPrecondInequalityConstraint void addPrecondInequalityConstraint(T fc, U pre): Undocumented in source. Be warned that the author may not have intended to support it.
copy auto copy(): Copies an instance of Opt to new instance.
create void create(Algorithm algorithm, uint n): Calls nlopt_create and sets its result to _opt.
forceStop void forceStop(): Force optimization to stop. Refer to http://ab-initio.mit.edu/wiki/index.php/NLopt_Reference#Forced_termination
getAlgorithm auto getAlgorithm(): Get Algorithm
getAlgorithmRaw auto getAlgorithmRaw(): Get Raw Algorithm
getDimension auto getDimension(): Get dimension
getFTolAbs auto getFTolAbs(): Gets the absolute tolerance for objective function f(x).
getFTolRel auto getFTolRel(): Gets the relative tolerance for objective function f(x).
getForceStop auto getForceStop(): Refer to http://ab-initio.mit.edu/wiki/index.php/NLopt_Reference#Forced_termination
getInitialStep void getInitialStep(T x, U dx)
void getInitialStep(double x, double dx): Gets initial step for derivative-free local optimization algorithms.
getLowerBounds void getLowerBounds(T lb)
void getLowerBounds(double lb): Get lower bounds
getMaxeval auto getMaxeval(): Gets the maximum number of evaluations.
getMaxtime auto getMaxtime(): Gets the maximum amount of time spent on optimization.
getOptRaw nlopt_opt getOptRaw(): Gets raw opt object
getPopulation auto getPopulation(): Get population in stochastic search algorithms.
getResult auto getResult(): Gets the result value.
getResultRaw auto getResultRaw(): Gets the raw result value.
getStopval auto getStopval(): Gets the Stopval.
getUpperBounds void getUpperBounds(T ub)
void getUpperBounds(double ub): Get upper bounds
getVectorStorage auto getVectorStorage(): Get vector storage.
getXTolAbs void getXTolAbs(T tol): Gets the absolute tolerance for x.
getXTolRel auto getXTolRel(): Gets the relative tolerance for x.
optimize void optimize(T x, double minf): Optimize
processResult void processResult(nlopt_result result): Processes a member of nlopt_result.
removeEqualityConstraints void removeEqualityConstraints(): Remove equality constraints
removeInequalityConstraints void removeInequalityConstraints(): Remove inequality constraints
setDefaultInitialStep void setDefaultInitialStep(T dx)
void setDefaultInitialStep(double dx): Sets default initial step for derivative-free local optimization algorithms.
setFTolAbs void setFTolAbs(double tol): Sets the absolute tolerance for objective function f(x).
setFTolRel void setFTolRel(double tol): Sets the relative tolerance for objective function f(x).
setForceStop void setForceStop(int val): Force optimization to stop with more information. Refer to http://ab-initio.mit.edu/wiki/index.php/NLopt_Reference#Forced_termination
setInitialStep void setInitialStep(T dx)
void setInitialStep(double dx): Sets initial step for derivative-free local optimization algorithms.
setLocalOptimizer void setLocalOptimizer(nlopt_opt local_opt)
void setLocalOptimizer(Opt local_opt): From NLopt Reference: "Some of the algorithms, especially MLSL and AUGLAG, use a different optimization algorithm as a subroutine, typically for local optimization."
setLowerBounds void setLowerBounds(T lb)
void setLowerBounds(double lb): Set lower bounds
setMaxObjective void setMaxObjective(T f, U f_data): Set Maximum Objective
setMaxeval void setMaxeval(int maxeval): Sets the maximum number of evaluations.
setMaxtime void setMaxtime(double maxtime): Sets the maximum amount of time spent on optimization.
setMinObjective void setMinObjective(T f, U f_data): Set Minimum Objective
setPopulation void setPopulation(uint pop): For use in stochastic search algorithms, size of initial population of random points. Default is that it is chosen heuristically by algorithm.
setPrecondMaxObjective void setPrecondMaxObjective(T f, U pre, V f_data): Set Maximum Objective with Pre-conditioned Hessian
setPrecondMinObjective void setPrecondMinObjective(T f, U pre, V f_data): Set Minimum Objective with Pre-conditioned Hessian
setStopval void setStopval(double stopval): Sets the Stopval.
setUpperBounds void setUpperBounds(T ub)
void setUpperBounds(double ub): Set upper bounds
setVectorStorage void setVectorStorage(uint M): For use with limited-memory algorithms that remember gradients from previous iterations.
setXTolAbs void setXTolAbs(T tol)
void setXTolAbs(double tol): Sets the absolute tolerance for x.
setXTolRel void setXTolRel(double tol): Sets the relative tolerance for x.
srand void srand(uint seed): Sets the seed for stochastic optimization.
srandTime void srandTime(): Re-sets the seed for stochastic optimization back to system time.

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