Operations Research methods: The Hungarian Method is a specialized algorithm used to optimally solve which class of problems?

Introduction / Context:
Operations Research provides algorithms tailored to problem structures. The Hungarian Method is a classic polynomial-time algorithm designed specifically for matching agents to tasks with minimum cost (or maximum profit). Recognizing the correct problem class helps practitioners choose the right tool quickly.

Given Data / Assumptions:

• We are selecting the problem category, not the solution technique name alone.
• Assignment problems feature a one-to-one assignment between two equal-sized sets.
• Costs or profits for each agent–task pairing are given in a matrix.

Concept / Approach:
The Hungarian Method transforms the cost matrix via row and column reductions, identifies zeros representing feasible assignments, and iteratively adjusts until an optimal one-to-one assignment is found. This is distinct from the Transportation Method (balanced shipping among sources and destinations) and from Simplex or Graphical methods used for general linear programming problems.

Step-by-Step Solution:
Identify structure: equal number of agents and tasks; one agent per task.Recognize matrix reductions and zero-covering steps characteristic of the Hungarian Method.Select “Assignment Method.”

Verification / Alternative check:
OR textbooks list the Hungarian Method under assignment problems, often alongside extensions (unbalanced, maximization).

Why Other Options Are Wrong:

• Graphical and Simplex: general LP methods.
• Transportation: solved via specialized heuristics and MODI/stepping-stone, not Hungarian.

Common Pitfalls:
Confusing assignment with transportation; assignment is a special case with one-to-one constraints.

Final Answer:
Assignment Method