Boosting the Performance of Iterative Flattening Search

Iterative Flattening search is a local search schema introduced for solving scheduling problems with a makespan minimization objective. It is an iterative two-step procedure, where on each cycle of the search a subset of ordering decisions on the critical path in the current solution are randomly retracted and then recomputed to produce a new solution. Since its introduction, other variations have been explored and shown to yield substantial performance improvement over the original formulation. In this spirit, we propose and experimentally evaluate further improvements to this basic local search schema. Specifically, we examine the utility of operating with a more flexible solution representation, and of integrating iterative-flattening search with a complementary tabu search procedure. We evaluate these extensions on large benchmark instances of the Multi-Capacity Job-Shop Scheduling Problem (MCJSSP) which have been used in previous studies of iterative flattening search procedures.

Publication type: 
Articolo
Author or Creator: 
Oddi
A.
Policella
N.
Cesta
Smith
S.F.
Publisher: 
Springer, Berlin , Germania
Source: 
Lecture notes in computer science 4733 (2007): 447–458. doi:10.1007/978-3-540-74782-6_39
info:cnr-pdr/source/autori:Oddi, A., Policella, N., Cesta, A., and Smith, S.F./titolo:Boosting the Performance of Iterative Flattening Search/doi:10.1007/978-3-540-74782-6_39/rivista:Lecture notes in computer science/anno:2007/pagina_da:447/pagina_a:458/i
Date: 
2007
Resource Identifier: 
http://www.cnr.it/prodotto/i/46947
https://dx.doi.org/10.1007/978-3-540-74782-6_39
info:doi:10.1007/978-3-540-74782-6_39
http://link.springer.com/chapter/10.1007/978-3-540-74782-6_39
Language: 
Eng
ISTC Author: 
Angelo Oddi's picture
Real name: 
Amedeo Cesta's picture
Real name: