Book contents
- Frontmatter
- Contents
- Preface
- 1 Introduction and Concepts
- 2 Large Neighborhood Search
- 3 Rounding, Propagation and Diving
- 4 The Feasibility Pump Family
- 5 Pivoting and Line Search Heuristics
- 6 Computational Study
- 7 Primal Heuristics for Mixed-Integer Nonlinear Programming
- 8 Machine Learning for Primal Heuristics
- Appendix Quiz Solutions
- References
- Index
3 - Rounding, Propagation and Diving
Published online by Cambridge University Press: 04 April 2025
- Frontmatter
- Contents
- Preface
- 1 Introduction and Concepts
- 2 Large Neighborhood Search
- 3 Rounding, Propagation and Diving
- 4 The Feasibility Pump Family
- 5 Pivoting and Line Search Heuristics
- 6 Computational Study
- 7 Primal Heuristics for Mixed-Integer Nonlinear Programming
- 8 Machine Learning for Primal Heuristics
- Appendix Quiz Solutions
- References
- Index
Summary
This chapter reviews the a large family of relatively cheap primal heuristics that generally try to convert infeasible solutions obtained by solving the continuous relaxation of a MIP into feasible solutions. The review is conducted by following three main concepts, namely that of rounding a fractional point to an integer one, that of propagating the logical implication of a decision on a variable to other variables, and that of diving, i.e., sequentially make decisions on variables. The combinations of these concepts are extensively analyzed.
- Type
- Chapter
- Information
- Primal Heuristics in Integer Programming , pp. 47 - 58Publisher: Cambridge University PressPrint publication year: 2025