With Complete Solutions
1). Optimization
Ans: maximizing or minimizing an objective function involving at least one variable
2). Linear programming
Ans: maximizing or minimizing an objective when the objective function AND all
constraints involve linear functions of the variables
3). 5 steps in formulating a linear program
Ans: (1) understand decision problem
(2) define decision variables
(3) express objective as a linear function of decision variables
(4) express constraints as a linear inequality
(5) identify upper or lower bounds of decision variables
4). Decision variables
Ans: variables that the decision maker can control to achieve their objective
5). Objective
Ans: the goal of the decision maker
6). Constraints
Ans: variables that restrict the decision maker's decision
7). Slack
Ans: the amount the left-hand side is lower than the right-hand side
8). Binding constraint
PaperStoc.com Page 1 of 8
, Ans: constraint's slack = 0 (LHS = RHS)
9). Non-binding constraint
Ans: constraint's slack > 0 (LHS < RHS)
10). Feasible solutions
Ans: solutions that satisfy all problem constraints
11). Infeasible solutions
Ans: solutions that violate at least one problem constraint
12). Optimal solution
Ans: feasible solution that meets the objective function (maximum or minimum value
reached)
13). Finding lp optimal solutions via graphing
Ans: (1) graph all constraints to determine the feasible plane
(2) graph isoquant lines (objective function) until you reach the point of tangency with the
feasible region
(2.5) system of equations where two constraint functions intersect
14). Redundant constraint
Ans: removal of a constraint does not affect the feasible region
15). Infeasible linear program
Ans: no feasible solution (no solution that meets all constraints)
PaperStoc.com Page 2 of 8