I’ve some query associated to the Linear Programming drawback :
1) If now we have an goal operate that must be maximized and let the possible area be unbounded such that there isn’t a finite optimum resolution. My query is what’s the which means of “finite” right here ?
2) If we have to remedy LP utilizing the simplex methodology , we have to remodel any constrain that’s written as an inequality equation to equality equation utilizing the addition of the slack variables , so my query is by doing this modification did we modify the issue ? I imply that now we have added an additional variable so I feel that now we have created a brand new constraint ?
3) Additionally to unravel the LP utilizing simplex methodology , we have to have a maximization drawback , so if now we have to attenuate an goal operate , on this case to remodel it to a maximization drawback all we have to do is to negate the coefficients ? for instance we have to reduce 3x+y=2 that is equal to maximizing -3x-y=2 ?