Effect of Seven Steps Approach on Simplex Method to Optimize the Mathematical Manipulation
Mohammad Rashid Hussain1, Mohammed Qayyum2, Mohammad Equebal Hussain3

1Mohammad Rashid Hussain, Department of Information Systems, College Of Computer Science, King Khalid University, Abha, KSA
2Mohammed Qayyum, Department of Computer Engineering, College Of Computer Science, King Khalid University, Abha, KSA
3Mohammad Equebal Hussain, Department of Computer Science, Suresh Gyan Vihar University, Jaipur, (R.J.), India.

Manuscript received on 04 January 2019 | Revised Manuscript received on 20 January 2019 | Manuscript published on 30 January 2019 | PP: 34-43 | Volume-7 Issue-5, January 2019 | Retrieval Number: E1948017519©BEIESP
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Abstract: The Simplex method is the most popular and successful method for solving linear programs. The objective function of linear programming problem (LPP) involves in the maximization and minimization problem with the set of linear equalities and inequalities constraints. There are different methods to solve LPP, such as simplex, dual-simplex, Big-M and two phase method. In this paper, an approach is presented to solve LPP with new seven steps process by choosing “key element rule” which is still widely used and remains important in practice. We propose a new technique i.e. seven step process in LPP for the simplex, dual-simplex, Big-M and two phase methods to get the solution with complexity reduction. The complexity reduction is done by eliminating the number of elementary row transformation operation in simplex tableau of identity matrix. By the proposed technique elementary transformation of operation has completely avoided and we can achieve the results in considerable duration
Keywords: Linear programming problem (LPP), Key element (KE), Key column (KC), Key row (KR), Profit per unit (PPU), Random variables (RV), Linear Gaussian Random variables (LGRV), standard deviation (SD), Probability Density Function (PDF)
Scope of the Article: Advanced Computing Architectures and New Programming Models