Linear programming terminology: the variable introduced with no real-world meaning, used solely to obtain an initial basic feasible solution, is called what?

Introduction / Context:
In linear programming, the simplex method often requires an initial basic feasible solution (BFS). When such a starting solution is not readily apparent from the constraints, the “two-phase” method or “Big-M” method introduces special variables to force feasibility temporarily. Understanding the purpose and nature of these variables is essential for interpreting algorithm steps correctly.

Given Data / Assumptions:

• We are dealing with LP feasibility and simplex initialization.
• The added variable does not represent a physical quantity.
• The goal is to remove it once feasibility is established.

Concept / Approach:
An artificial variable is appended to constraints to create an initial identity basis so that the simplex method can start. In Phase I of the two-phase method, the objective is to minimize the sum of artificial variables, driving them to zero and yielding a feasible solution in the original variables. If they cannot be driven to zero, the LP is infeasible. With the Big-M approach, large penalties in the objective discourage artificial variables from remaining positive in the optimal solution.

Step-by-Step Solution:

Verification / Alternative check:
Standard LP textbooks describe artificial variables as computational devices without physical interpretation, introduced purely to obtain an initial BFS.

Why Other Options Are Wrong:

• Basis/basic variable: general simplex terms, but not the special introduced variable.
• Algorithm: refers to the method (simplex/two-phase), not the variable.
• None: incorrect because “artificial variable” is the precise term.

Common Pitfalls:
Assigning a physical meaning to artificial variables; forgetting to remove them before interpreting the final solution.

Final Answer:
artificial variable