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The convex hull heuristic for nonlinear integer programming problems with linear constraints and application to quadratic 0–1 problems
| Content Provider | Semantic Scholar |
|---|---|
| Author | Guignard, M. M. Ahlatçioglu, Aykut |
| Copyright Year | 2020 |
| Abstract | The convex hull heuristic is a heuristic for mixed-integer programming problems with a nonlinear objective function and linear constraints. It is a matheuristic in two ways: it is based on the mathematical programming algorithm called simplicial decomposition, or SD (von Hohenbalken in Math Program 13:49–68, 1977), and at each iteration, one solves a mixed-integer programming problem with a linear objective function and the original constraints, and a continuous problem with a nonlinear objective function and a single linear constraint. Its purpose is to produce quickly feasible and often near optimal or optimal solutions for convex and nonconvex problems. It is usually multi-start. We have tested it on a number of hard quadratic 0–1 optimization problems and present numerical results for generalized quadratic assignment problems, cross-dock door assignment problems, quadratic assignment problems and quadratic knapsack problems. We compare solution quality and solution times with results from the literature, when possible. |
| Starting Page | 1 |
| Ending Page | 15 |
| Page Count | 15 |
| File Format | PDF HTM / HTML |
| DOI | 10.1007/s10732-019-09433-w |
| Alternate Webpage(s) | http://www.optimization-online.org/DB_FILE/2019/11/7468.pdf |
| Alternate Webpage(s) | https://doi.org/10.1007/s10732-019-09433-w |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
