Linear Programming
Rajeev Bhattacharya
Abstract
Rajeev Bhattacharya
Abstract
An optimization problem with a linear objective function and linear constraints is called a linear programming problem. A vector satisfying the inequality and non-negative constraints is called a feasible solution. If a linear programming problem and its dual have feasible solutions, then both have optimal solutions, and the value of the optimal solution is the same for both. If either the program or its dual does not have a feasible solution, then neither has an optimal vector. The simplex method is a simple method of solving a linear programming problem.
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An optimization problem with a linear objective function and linear constraints is called a linear programming problem. A vector satisfying the inequality and non-negative constraints is called a feasible solution. If a linear programming problem and its dual have feasible solutions, then both have optimal solutions, and the value of the optimal solution is the same for both. If either the program or its dual does not have a feasible solution, then neither has an optimal vector. The simplex method is a simple method of solving a linear programming problem.
Key concepts: Linear-fractional programming, Linear programming, Simplex algorithm, Mathematical optimization, Criss-cross algorithm, Mathematics, Simple (philosophy), Dual (grammatical number)