pyepo.model.grb

Optimization Model based on GurobiPy

Submodules

Classes

`optGrbModel`	This is an abstract class for Gurobi-based optimization model
`shortestPathModel`	This class is optimization model for shortest path problem
`knapsackModel`	This class is optimization model for knapsack problem
`tspGGModel`	This class is optimization model for traveling salesman problem based on Gavish–Graves (GG) formulation.
`tspDFJModel`	This class is optimization model for traveling salesman problem based on Danzig–Fulkerson–Johnson (DFJ) formulation and
`tspMTZModel`	This class is optimization model for traveling salesman problem based on Miller-Tucker-Zemlin (MTZ) formulation.
`portfolioModel`	This class is an optimization model for portfolio problem

Package Contents

class pyepo.model.grb.optGrbModel

Bases: pyepo.model.opt.optModel

This is an abstract class for Gurobi-based optimization model

_model

Gurobi model

Type:: GurobiPy model

__repr__()

property num_cost: number of cost to be predicted

setObj(c)

A method to set objective function

Parameters:: c (np.ndarray / list) – cost of objective function

solve()

A method to solve model

Returns:: optimal solution (list) and objective value (float)
Return type:: tuple

copy()

A method to copy model

Returns:: new copied model
Return type:: optModel

addConstr(coefs, rhs)

A method to add new constraint

Parameters:

coefs (np.ndarray / list) – coeffcients of new constraint
rhs (float) – right-hand side of new constraint

Returns:

new model with the added constraint

Return type:

optModel

class pyepo.model.grb.shortestPathModel(grid)

Bases: pyepo.model.grb.grbmodel.optGrbModel

This class is optimization model for shortest path problem

_model

Gurobi model

Type:: GurobiPy model

grid

Size of grid network

Type:: tuple of int

arcs

List of arcs

Type:: list

grid

arcs = []

_getArcs()

A method to get list of arcs for grid network

Returns:: arcs
Return type:: list

_getModel()

A method to build Gurobi model

Returns:: optimization model and variables
Return type:: tuple

class pyepo.model.grb.knapsackModel(weights, capacity)

Bases: pyepo.model.grb.grbmodel.optGrbModel

This class is optimization model for knapsack problem

_model

Gurobi model

Type:: GurobiPy model

weights

Weights of items

Type:: np.ndarray / list

capacity

Total capacity

Type:: np.ndarray / listy

items

List of item index

Type:: list

weights

capacity

items

_getModel()

A method to build Gurobi model

Returns:: optimization model and variables
Return type:: tuple

relax(): A method to get linear relaxation model

class pyepo.model.grb.tspGGModel(num_nodes)

Bases: tspABModel

This class is optimization model for traveling salesman problem based on Gavish–Graves (GG) formulation.

_model

Gurobi model

Type:: GurobiPy model

num_nodes

Number of nodes

Type:: int

edges

List of edge index

Type:: list

_getModel()

A method to build Gurobi model

Returns:: optimization model and variables
Return type:: tuple

setObj(c)

A method to set objective function

Parameters:: c (list) – cost vector

solve(): A method to solve model

addConstr(coefs, rhs)

A method to add new constraint

Parameters:

coefs (ndarray) – coeffcients of new constraint
rhs (float) – right-hand side of new constraint

Returns:

new model with the added constraint

Return type:

optModel

relax(): A method to get linear relaxation model

class pyepo.model.grb.tspDFJModel(num_nodes)

Bases: tspABModel

This class is optimization model for traveling salesman problem based on Danzig–Fulkerson–Johnson (DFJ) formulation and constraint generation.

_model

Gurobi model

Type:: GurobiPy model

num_nodes

Number of nodes

Type:: int

edges

List of edge index

Type:: list

_getModel()

A method to build Gurobi model

Returns:: optimization model and variables
Return type:: tuple

static _subtourelim(model, where): A static method to add lazy constraints for subtour elimination

setObj(c)

A method to set objective function

Parameters:: c (list) – cost vector

solve(): A method to solve model

addConstr(coefs, rhs)

A method to add new constraint

Parameters:

coefs (ndarray) – coeffcients of new constraint
rhs (float) – right-hand side of new constraint

Returns:

new model with the added constraint

Return type:

optModel

class pyepo.model.grb.tspMTZModel(num_nodes)

Bases: tspABModel

This class is optimization model for traveling salesman problem based on Miller-Tucker-Zemlin (MTZ) formulation.

_model

Gurobi model

Type:: GurobiPy model

num_nodes

Number of nodes

Type:: int

edges

List of edge index

Type:: list

_getModel()

A method to build Gurobi model

Returns:: optimization model and variables
Return type:: tuple

setObj(c)

A method to set objective function

Parameters:: c (list) – cost vector

solve(): A method to solve model

addConstr(coefs, rhs)

A method to add new constraint

Parameters:

coefs (ndarray) – coeffcients of new constraint
rhs (float) – right-hand side of new constraint

Returns:

new model with the added constraint

Return type:

optModel

relax(): A method to get linear relaxation model

class pyepo.model.grb.portfolioModel(num_assets, covariance, gamma=2.25)

Bases: pyepo.model.grb.grbmodel.optGrbModel

This class is an optimization model for portfolio problem

_model

Gurobi model

Type:: GurobiPy model

num_assets

number of assets

Type:: int

covariance

covariance matrix of the returns

Type:: numpy.ndarray

risk_level

risk level

Type:: float

num_assets

covariance

risk_level

_getRiskLevel(gamma)

A method to calculate the risk level

Returns:: risk level
Return type:: float

_getModel()

A method to build Gurobi model

Returns:: optimization model and variables
Return type:: tuple