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Linearization method for a class of multiplicative programming with exponent
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DOI：10.1016/j.amc.2006.05.074.png)
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Abstract
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This paper presents a global optimization algorithm for a class of multiplicative programming with exponent under multiplicative constraints (MPE). By utilizing equivalent problem of MPE in the sense that they have the same optimal solution, tangential hypersurfaces and concave envelope approximations a linear relaxation of equivalent problem is received. Thus the initial nonconvex programming problem (MPE) is reduced to a sequence of linear programming problems through the successive refinement of a linear relaxation of feasible region of the objective function. The proposed algorithm is convergent to the globally optimal solution of MPE by means of the subsequent solutions of a series of linear programming problems. Numerical results indicate that the proposed algorithm is extremely robust and can be used successfully to solve global minimum of MPE on microcomputer. (c) 2006 Elsevier Inc. All rights reserved.
Keywords:
multiplicative programming
global optimization
linear relaxation
branch and bound
Journal
IF:
3.4
Papers:
2.3W
Citations:
3.3W
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