EconPapers    
Economics at your fingertips  
 

Constraint-Based Local Search

L. Michel () and P. Van Hentenryck ()
Additional contact information
L. Michel: University of Connecticut
P. Van Hentenryck: Georgia Institute of Technology, School of Industrial and Systems Engineering

Chapter 15 in Handbook of Heuristics, 2025, pp 389-426 from Springer

Abstract: Abstract Constraint-Based Local Search emerged in the last decade as a framework for declaratively expressing hard combinatorial optimization problems and solving them with local search techniques. It delivers tools to practitioners that enable them to quickly experiment with multiple models, heuristics, and meta-heuristics, focusing on their application rather than the delicate minutiae of producing a competitive implementation. At its heart, the declarative models are reminiscent of the modeling facilities familiar to constraint programming, while the underlying computational model heavily depends on incrementality. The net result is a platform capable of delivering competitive local search solutions at a fraction of the efforts needed with a conventional approach delivering model-and-run to local search users.

Keywords: Local Search; Model; Declarative; Incremental; Solver (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-032-00385-0_7

Ordering information: This item can be ordered from
http://www.springer.com/9783032003850

DOI: 10.1007/978-3-032-00385-0_7

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().

 
Page updated 2026-02-09
Handle: RePEc:spr:sprchp:978-3-032-00385-0_7