In this article,the authors discuss the optimal conditions of the linearfractionalprogrammingproblem and prove that a locally optional solution is a globally optional solution and the locally optimal solution can be...
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In this article,the authors discuss the optimal conditions of the linearfractionalprogrammingproblem and prove that a locally optional solution is a globally optional solution and the locally optimal solution can be attained at a basic feasible solution withconstraint condition.
This paper is concerned with a practical algorithm for solving low rank linear multiplicative programmingproblems and low rank linear fractional programming problems. The former is the minimization of the sum of the ...
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This paper is concerned with a practical algorithm for solving low rank linear multiplicative programmingproblems and low rank linear fractional programming problems. The former is the minimization of the sum of the product of two linear functions while the latter is the minimization of the sum of linearfractional functions over a polytope. Both of these problems are nonconvex minimization problems with a lot of practical applications. We will show that these problems can be solved in an efficient manner by adapting a branch and bound algorithm proposed by Androulakis-Maranas-Floudas for nonconvex problems containing products of two variables. Computational experiments show that this algorithm performs much better than other reported algorithms for these class of problems.
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