Lesson Summary Subtract row minima. Subtract column minima. Cover all zeros with the minimum number of lines. If the number of lines is equal to the number of rows or columns in your matrix, stop here. Create additional zeros by finding the smallest element - call it c - that isn't covered by a line.
For example, suppose an accounts officer has 4 subordinates and 4 tasks. The subordinates differ in efficiency and take different time to perform each task. If one task is to be assigned to one person in such a way that the total person hours are minimised, the problem is called an assignment problem.
The Hungarian method is a simple way to solve assignment problems.
The Hungarian method, also known as the Kuhn-Munkres algorithm, is a computational technique used to solve the assignment problem in polynomial time. It's a precursor to many primal-dual methods used today.
The Hungarian method is a simple way to solve assignment problems.
The assignment problem in the general form can be stated as follows: “Given n facilities, n jobs and the effectiveness of each facility for each job, the problem is to assign each facility to one and only one job in such a way that the measure of effectiveness is optimised (Maximised or Minimised).”
An 'Assignment Method' in computer science refers to the techniques used to allocate resources or tasks to different entities. It includes methods like simple random assignment and random assignments from blocks or strata.
An assignment is a piece of (academic) work or task. It provides opportunity for students to learn, practice and demonstrate they have achieved the learning goals. It provides the evidence for the teacher that the students have achieved the goals.
The assignment method is used to determine what resources are assigned to which department, machine, or center of operation in the production process. The goal is to assign resources in such a way to enhance production efficiency, control costs, and maximize profits.
The Generalized Assignment Problem has shown to be NP-hard and therefore efficient algorithms are needed, especially for large problems.