Abstract
In this paper a new approach for obtaining an approximation global optimum solution of zero-one nonlinear programming (0-1 NP) problem which we call it Parametric Linearization Approach (P.L.A) is proposed. By using this approach the problem is transformed to a sequence of linear programming problems. The approximately solution of the original 0-1 NP problem is obtained based on the optimum values of the objective functions of this sequence of linear programming problems defined by (P.L.A).
Highlights
Integer programming is one of the most interesting and difficult research areas in mathematical programming and operations research
At first we consider zero-one nonlinear programming problem in which the discrete constraint are replaced with continuous ones
0 j 1, n, In this paper we present a new approach call it parametric linearization approach for finding the approxi
Summary
Integer programming is one of the most interesting and difficult research areas in mathematical programming and operations research. A number of research paper dealing with reliability optimization problems are reported in the literature These are integer programming problems with nonlinear separable objective function and nonlinear multi choice constrained [5,6]. A developed optimization method for solving integer nonlinear programming problem (INLP) with 0-1 variable could be found in [7]. Hanssen and Meyer in [13] compare different ways for linearization the unconstraint quadratic zero-one minimization problem This approaches involves to increase the number of variables and constraints. At first we consider zero-one nonlinear programming problem in which the discrete constraint are replaced with continuous ones. The third section contain a description of using the parametric linearization approximation for solving zero-one nonlinear programming problem.
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