Abstract
Spreadsheets have evolved into sophisticated computation and presentation tools that are versatile, easy to use and accessible. This paper illustrates the power of macro spreadsheets by presenting an advanced macro program that finds the solution of linear programming problems using the simplex method. As an example, the transportation problem is solved with different numbers of origins and destinations. Taking advantage of some programming features of spreadsheets, the program uses an improved pivotal elimination subroutine to reduce the execution time drastically. The macro program is described and computational results based on some examples are given. Scope and purpose Linear programming is a well-known discipline with many real-word applications. Real-world examples solved by linear programming techniques include the transportation problem in which the minimum cost of transportation is to be found when a certain quantity of product is to be shipped from one location to another. The most common optimization technique for solving these types of problems is the simplex method. The purpose of this paper is to present an advanced macro spreadsheet program that finds the solution of the transportation problem using the simplex method with an improved elimination subroutine. As a result the computation time is reduced drastically, hence demonstrating the potential of the program for an efficient and real-time application of the program to this type and other practical problems.
| Original language | English |
|---|---|
| Pages (from-to) | 233-243 |
| Number of pages | 11 |
| Journal | Computers and Operations Research |
| Volume | 27 |
| Issue number | 3 |
| DOIs | |
| State | Published - Mar 2000 |
Bibliographical note
Funding Information:The author wish to acknowledge the support of King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia.
Keywords
- Linear programming
- Macro
- Simplex method
- Spreadsheet
- Transportation problem
ASJC Scopus subject areas
- General Computer Science
- Modeling and Simulation
- Management Science and Operations Research