RAMP algorithms for the capacitated facility location problem

In this paper, we address the Capacitated Facility Location Problem (CFLP) in which the assignment of facilities to customers must ensure enough facility capacity and all the customers must be served. We propose both sequential and parallel Relaxation Adaptive Memory Programming approaches for the C...

Full description

Saved in:
Bibliographic Details
Published inAnnals of mathematics and artificial intelligence Vol. 89; no. 8-9; pp. 799 - 813
Main Authors Matos, Telmo, Oliveira, Óscar, Gamboa, Dorabela
Format Journal Article
LanguageEnglish
Published Cham Springer International Publishing 01.09.2021
Springer
Springer Nature B.V
Subjects
Algorithms
Artificial Intelligence
Complex Systems
Computer Science
Costs
Customers
Heuristic
Industrial locations
Linear programming
Mathematics
Operations research
Site selection
Solution space
Variables
Facility location
Lagrangean relaxation
Adaptive memory programming
RAMP
Online AccessGet full text
ISSN1012-2443
1573-7470
DOI10.1007/s10472-021-09757-z

Cover

More Information
Summary:In this paper, we address the Capacitated Facility Location Problem (CFLP) in which the assignment of facilities to customers must ensure enough facility capacity and all the customers must be served. We propose both sequential and parallel Relaxation Adaptive Memory Programming approaches for the CFLP, combining a Lagrangean subgradient search with an improvement method to explore primal-dual relationships to create advanced memory structures that integrate information from both primal and dual solution spaces. Computational experiments of the effectiveness of this approach are presented and discussed.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:1012-2443
1573-7470
DOI:10.1007/s10472-021-09757-z