Abstract
Conventional methods of solving nonconvex separable programming (NSP) problems by mixed integer programming methods requires adding numerous 0-1 variables. In this work, we present a new method of deriving the global optimum of a NSP program using less number of 0-1 variables. A separable function is initially expressed by a piecewise linear function with summation of absolute terms. Linearizing these absolute terms allows us to convert a NSP problem into a linearly mixed 0-1 program solvable for reaching a solution which is extremely close to the global optimum.
| Original language | English |
|---|---|
| Pages (from-to) | 275-292 |
| Number of pages | 18 |
| Journal | European Journal of Operational Research |
| Volume | 117 |
| Issue number | 2 |
| DOIs | |
| State | Published - 1 Sep 1999 |