initState

Generate an initial feasible solution by solving a linear programming with binary variables

The sampl.mcmc function creates samples of the feasible region of a knapsack problem with both equalities and inequalities constraints.

Chin Soon Lim

KnapsackSampling

Generate Feasible Samples of a Knapsack Problem

initState function

<dl><dt>numVar</dt>
<dd>- number of variables</dd>
<dt>objVec</dt>
<dd>- objective function as a numeric vector</dd>
<dt>constraints</dt>
<dd>- a list of list of constraints with constr.mat, constr.dir, constr.rhs in each sublist</dd></dl>

Arguments

Generate an initial feasible solution by solving a linear programming with binary variables — initState

<dl>

<dt>numVar</dt>
<dd>- number of variables</dd>


<dt>objVec</dt>
<dd>- objective function as a numeric vector</dd>


<dt>constraints</dt>
<dd>- a list of list of constraints with constr.mat, constr.dir, constr.rhs in each sublist</dd>

</dl>

initState: Generate an initial feasible solution by solving a linear programming with binary variables

Description

Usage

Value

Arguments

Examples