
handle: 11441/29474 , 11441/138654
Many problems in engineering design involve the use of nonlinearities and some integer variables. Methods based on test sets have been proposed to solve some particular problems with integer variables, but they have not been frequently applied because of computation costs. The walk-back procedure based on a test set gives an exact method to obtain an optimal point of an integer programming problem with linear and nonlinear constraints, but the calculation of this test set and the identification of an optimal solution using the test set directions are usually computationally intensive. In problems for which obtaining the test set is reasonably fast, we show how the effectiveness can still be substantially improved. This methodology is presented in its full generality and illustrated on two specific problems: (1) minimizing cost in the problem of scheduling jobs on parallel machines given restrictions on demands and capacity, and (2) minimizing cost in the series parallel redundancy allocation problem, given a target reliability. Our computational results are promising and suggest the applicability of this approach to deal with other problems with similar characteristics or to combine it with mainstream solvers to certify optimality
Ministerio de Ciencia e Innovación MTM2013-46962- C2-1-P
Ministerio de Ciencia e Innovación MTM2010-19336
Ministerio de Ciencia e Innovación MTM2010-19576
Junta de Andalucía FQM- 5849
FEDER
Non-linear Integer Programming, nonlinear integer programming, Non-linear integer programming, test set, Nonlinear programming, Test set, chance constrained programming, Integer programming, Gröbner basis, Chance constrained programming
Non-linear Integer Programming, nonlinear integer programming, Non-linear integer programming, test set, Nonlinear programming, Test set, chance constrained programming, Integer programming, Gröbner basis, Chance constrained programming
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 2 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
