Probabilistic Constrained Linear Programming: Duality Theory

Networks ◽  
2008 ◽  
Vol 52 (4) ◽  
pp. 299-306 ◽  
Author(s):  
Charles J. Colbourn ◽  
Gaetano Quattrocchi ◽  
Violet R. Syrotiuk

2013 ◽  
Vol 2013 ◽  
pp. 1-10 ◽  
Author(s):  
Xue-Gang Zhou ◽  
Bing-Yuan Cao

A simplicial branch and bound duality-bounds algorithm is presented to globally solving the linear multiplicative programming (LMP). We firstly convert the problem (LMP) into an equivalent programming one by introducingpauxiliary variables. During the branch and bound search, the required lower bounds are computed by solving ordinary linear programming problems derived by using a Lagrangian duality theory. The proposed algorithm proves that it is convergent to a global minimum through the solutions to a series of linear programming problems. Some examples are given to illustrate the feasibility of the present algorithm.


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