Master Transportation Problem Algorithm

Learn the algorithm with Applications for Minimisation, Maximisation, Balanced, Unbalanced Problems

What you'll learn
You will learn the basic tools of Operations Research, namely the Transportation Problem
The Transportation Problem algorithm is ideally applied where there are several origins and several destnations and goods have to sent over these routes.
You will learn to solve a variety of problems including unbalanced problems, degenerate problems maximization problems
You will learn the technique of Transportation Problem where in phase 1 we obtain the Initial Feasible Solution or Basic Feasible Solution
The Initial solution needs to be improved in phase II of the problem and improve the same till optimality is reached in second phase

Requirements
There are no prerequisites for the course
You need a computer with internet connectivity
you need a simple calculator
You need knowledge of school level maths

Description
I am a professor of Operations Research, teaching this subject from 1986 onwards. Linear Programming, Assignment Problem, Transportation Problem, Networking Techniques, Game Theory are some of the major algorithms in Operations Research. My attempt, over the years has been to teach without involving great deal of mathematics, so that the student without any math background can also understand the algorithm easily. In the initial phase I launched the courses on Linear Programming, Assignment Problem, Transportation Problem, Sequencing at one go. This 10 hour video course will give you complete insight into solving a Transportation Problem. Both minimization and maximization cases will be covered, including the more complex degenerate problems. The initial Feasible solution to a transportation problem will be obtained by one of the three methods namely North West Cornet Rule, Least Cost Method or Vogel's Approximation Method. In the second phase, we will cover the MoDi or Modified Distribution Method. The solution to the unbalanced Transportation Problem has been covered. A representative problem of applying the algorithm to a scheduling problem has been covered in the course. In the case of the this algorithm, step by step approach to solving the problems has been introduced, starting with what I call as ‘prechecks’. The idea is that the student should be able to formulate and solve the problem on her own. While both these algorithms are for minimization, the problems for maximization can also be solved by converting them into minimization first. Examples of this effect are covered. I hope that the student will be able to formulate a given situation as one of these algorithm problems and solve it on his own.

Who this course is for:
Anyone who wants to learn about Operations Research as applied to the Transportation Problem (TP),Scholars and academicians looking to learn more about (TP),Anyone doing Engineering, with Operations Research as one of the subjects,MBA and BMS Scholars with Operations Research as subject.,BBA, CPA scholars with Operations Research as a subject.