scholarly journals A Computer Oriented Method for Solving Transportation Problem

2015 ◽  
Vol 63 (1) ◽  
pp. 1-7
Author(s):  
Sharmin Afroz ◽  
M Babul Hasan
Keyword(s):  
Linear Programming ◽  
Computer Program ◽  
Simplex Method ◽  
Transportation Problem ◽  
Linear Program ◽  
Numerical Examples ◽  
Linear Programming Problems

In this paper, an algorithm and its computer oriented program have been developed for solving transportation programming (TP) reducing it into a linear program (LP). After formulating it into linear programming problems the number of variables becomes large. It then, becomes more difficult and time-consuming if it is done manually with simplex method. By using the computer program the solution can be found in a shorter time. It will be shown that a TP with a large number of variables can be solved in few seconds by using this method. A number of numerical examples are presented to demonstrate the method developed in this research. DOI: http://dx.doi.org/10.3329/dujs.v63i1.21758 Dhaka Univ. J. Sci. 63(1): 1-7, 2015 (January)

scholarly journals A Simplified Novel Technique for Solving Linear Programming Problems with Triangular Fuzzy Variables via Interval Linear Programming Problems

2021 ◽  
pp. 82-93
Author(s):  
Ladji Kané ◽  
Lassina Diabaté ◽  
Daouda Diawara ◽  
Moussa Konaté ◽  
Souleymane Kané
Keyword(s):  
Linear Programming ◽  
Simplex Method ◽  
Real Problem ◽  
Interval Linear Programming ◽  
Numerical Examples ◽  
Fuzzy Variables ◽  
Novel Technique ◽  
Interval Linear ◽  
Linear Programming Problems

This study proposes a novel technique for solving Linear Programming Problems with triangular fuzzy variables. A modified version of the well-known simplex method and the Existing Method for Solving Interval Linear Programming problems are used for solving linear programming problems with triangular fuzzy variables. Furthermore, for illustration, some numerical examples and one real problem are used to demonstrate the correctness and usefulness of the proposed method. The proposed algorithm is flexible, easy, and reasonable.

THE DS/AHP METHOD UNDER PARTIAL INFORMATION ABOUT CRITERIA AND ALTERNATIVES BY SEVERAL LEVELS OF CRITERIA

2012 ◽  
Vol 11 (02) ◽  
pp. 307-326 ◽  
Author(s):  
LEV V. UTKIN ◽  
NATALIA V. SIMANOVA
Keyword(s):  
Linear Programming ◽  
Incomplete Information ◽  
Decision Problem ◽  
Partial Information ◽  
Decision Makers ◽  
Ahp Method ◽  
Numerical Examples ◽  
Finite Set ◽  
Linear Programming Problems ◽  
Decision Alternatives

An extension of the DS/AHP method is proposed in the paper. It takes into account the fact that the multi-criteria decision problem might have several levels of criteria. Moreover, it is assumed that expert judgments concerning the criteria are imprecise and incomplete. The proposed extension also uses groups of experts or decision makers for comparing decision alternatives and criteria. However, it does not require assigning favorability values for groups of decision alternatives and criteria. The computation procedure for processing and aggregating the incomplete information about criteria and decision alternatives is reduced to solving a finite set of linear programming problems. Numerical examples explain in detail and illustrate the proposed approach.

scholarly journals Statistical Methods for Solving Transportation Problems

2019 ◽  
Vol 25 (2) ◽  
pp. 10-13
Author(s):  
Alina Baboş
Keyword(s):  
Linear Programming ◽  
Statistical Methods ◽  
Approximation Method ◽  
Transportation Problem ◽  
Feasible Solution ◽  
Basic Feasible Solution ◽  
Statistical Tools ◽  
Numerical Examples ◽  
North West ◽  
Shipping Cost

Abstract Transportation problem is one of the models of Linear Programming problem. It deals with the situation in which a commodity from several sources is shipped to different destinations with the main objective to minimize the total shipping cost. There are three well-known methods namely, North West Corner Method Least Cost Method, Vogel’s Approximation Method to find the initial basic feasible solution of a transportation problem. In this paper, we present some statistical methods for finding the initial basic feasible solution. We use three statistical tools: arithmetic and harmonic mean and median. We present numerical examples, and we compare these results with other classical methods.

A New Dynamic Basis Algorithm for Solving Linear Programming Problems for Engineering Design

1988 ◽  
Author(s):  
Y. Wang ◽  
E. Sandgren
Keyword(s):  
Linear Programming ◽  
Simplex Method ◽  
Inequality Constraints ◽  
Upper And Lower Bounds ◽  
Programming Algorithm ◽  
Active Constraint ◽  
Design Variables ◽  
Artificial Variable ◽  
Linear Programming Problems ◽  
Revised Simplex Method

Abstract A new linear programming algorithm is proposed which has significant advantages compared to the traditional simplex method. The search direction generated which is always along a common edge of the active constraint set, is used to locate candidate constraints, and can be used to modify the current basis. The dimension of the basis begins at one and dynamically increases but remains less than or equal to the number of design variables. This is true regardless of the number of inequality constraints present including upper and lower bounds. The proposed method can operate equally well from a feasible or infeasible point. The pivot operation and artificial variable strategy of the simplex method are not used. Examples are presented and results are compared with a traditional revised simplex method.

Reduction-by-Projection Method for Linear Programming Problems

2014 ◽  
Vol 672-674 ◽  
pp. 1968-1971
Author(s):  
Xue Tong ◽  
Jun Qiang Wei
Keyword(s):  
Linear Programming ◽  
Linear Systems ◽  
Integer Linear Programming ◽  
Projection Method ◽  
Simplex Method ◽  
New Method ◽  
Linear Programming Problems

This paper defines the projection of algebic systems, and studies the projecting algorithm for linear systems. As its application, a new method is given to solve linear programming problems, which is called reduction-by-projection method. For many problems, especially when the problems have many constraint conditions in comparison with the number of their variables, the method needs less computation than simplex method and others. The great advantage of the method is shown when solving the integer linear programming problems.

A dual simplex method for grey linear programming problems based on duality results

2020 ◽  
Vol 10 (2) ◽  
pp. 145-157
Author(s):  
Davood Darvishi Salookolaei ◽  
Seyed Hadi Nasseri
Keyword(s):  
Linear Programming ◽  
Programming Problem ◽  
Linear Programming Problem ◽  
Simplex Method ◽  
Dual Problem ◽  
Complementary Slackness ◽  
Dual Simplex Method ◽  
Content Type ◽  
Dual Simplex ◽  
Linear Programming Problems

PurposeFor extending the common definitions and concepts of grey system theory to the optimization subject, a dual problem is proposed for the primal grey linear programming problem.Design/methodology/approachThe authors discuss the solution concepts of primal and dual of grey linear programming problems without converting them to classical linear programming problems. A numerical example is provided to illustrate the theory developed.FindingsBy using arithmetic operations between interval grey numbers, the authors prove the complementary slackness theorem for grey linear programming problem and the associated dual problem.Originality/valueComplementary slackness theorem for grey linear programming is first presented and proven. After that, a dual simplex method in grey environment is introduced and then some useful concepts are presented.

An Extended Simplex Algorithm for Linear Programming

2012 ◽  
Vol 532-533 ◽  
pp. 1626-1630
Author(s):  
Guo Guang Zhang
Keyword(s):  
Linear Programming ◽  
Simplex Method ◽  
Feasible Solution ◽  
Simplex Algorithm ◽  
Linear Program ◽  
Problem Solution ◽  
Test Number ◽  
The Times ◽  
Definition Of

Simplex method is one of the most useful methods to solve linear program. However, before using the simplex method, it is required to have a base feasible solution of linear program and the linear program is changed to thetypical form. Although there are some methods to gain the base feasible solution of linear program, artificial variablesare added and the times of calculating are increased with these calculations. In this paper, an extended algorithm of the simplex algorithm is established, the definition of feasible solution in the new algorithm is expended, the test number is not the same sign in the process of finding problem solution. Explained the principle of the new algorithm and showed results of LP problems calculated by the new algorithm.

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