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1st Student's Major

Computer Information Science

1st Student's College

Science, Engineering and Technology

Students' Professional Biography

Tapojit Kumar is a senior year student in the Computer and Information Sciences department at Minnesota State University, Mankato, MN. His areas of interest include Combinatorial Optimization, Parallel Processing, Network Security and Algorithm Analysis.

Mentor's Name

Susan Schilling

Mentor's Email Address

susan.schilling@mnsu.edu

Mentor's Department

Computer Information Science

Mentor's College

Science, Engineering and Technology

Abstract

The Transportation Problem is a classic Operations Research problem where the objective is to determine the schedule for transporting goods from source to destination in a way that minimizes the shipping cost while satisfying supply and demand constraints. Although it can be solved as a Linear Programming problem, other methods exist. Linear Programming makes use of the Simplex Method, an algorithm invented to solve a linear program by progressing from one extreme point of the feasible polyhedron to an adjacent one. The algorithm contains tactics like pricing and pivoting. For a Transportation Problem, a simplified version of the regular Simplex Method can be used, known as the Transportation Simplex Method. This paper will discuss the functionality of both of these algorithms, and compare their run-time and optimized values with a heuristic method called the Genetic Algorithm. Genetic Algorithms, pioneered by John Holland, are algorithms that use mechanisms similar to those of natural evolution to encourage the survival of the best intermediate solutions. The objective of the study was to find out how these algorithms behave in terms of accuracy and speed when a large-scale problem is being solved.

Creative Commons License

Creative Commons Attribution-Noncommercial 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial 4.0 License

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