Article
المجلة العلمية :
Journal of Experimental & Theoretical Artificial Intelligence (JETAI)
ISSN : 1362-3079
الناشر :
Taylor & Francis
معلومات
الفترة : January 2018
المجلد : 30 العدد : 3
الصفحات : 369-387
التفاصيل
A GRASP algorithm based new heuristic for the capacitated location routing problem
Imene Ferdi Abdesslem Layeb
AbstractIn this paper, the capacitated location-routing problem (CLRP) is studied. CLRP is composed of two hard optimisation problems: the facility location problem and the vehicle routing problem. The objective of CLRP is to determine the best location of multiple depots with their vehicle routes such that the total cost of the solution is minimal. To solve this problem, we propose a greedy randomised adaptive search procedure. The proposed method is based on a new heuristic to construct a feasible CLRP solution, and then a local search-based simulated annealing is used as improvement phase. We have used a new technique to construct the clusters around the depots. To prove the effectiveness of our algorithm, several LRP instances are used. The results found are very encouraging.
الكلمات المفتاحية :
Optimisation problems Capacitated location-routing problem Constructive heuristics GRASP Local search
مرجع الإقتباس :
misc-lab-177
DOI :
10.1080/0952813X.2017.1421268
الرابط :
Texte intégral
ACM :
I. Ferdi and A. Layeb. 2018. A GRASP algorithm based new heuristic for the capacitated location routing problem. Journal of Experimental & Theoretical Artificial Intelligence (JETAI), 30, 3 (January 2018), Taylor & Francis, 369-387. DOI: https://doi.org/10.1080/0952813X.2017.1421268.
APA :
Ferdi, I. & Layeb, A. (2018, January). A GRASP algorithm based new heuristic for the capacitated location routing problem. Journal of Experimental & Theoretical Artificial Intelligence (JETAI), 30(3), Taylor & Francis, 369-387. DOI: https://doi.org/10.1080/0952813X.2017.1421268
IEEE :
I. Ferdi and A. Layeb, "A GRASP algorithm based new heuristic for the capacitated location routing problem". Journal of Experimental & Theoretical Artificial Intelligence (JETAI), vol. 30, no. 3, Taylor & Francis, pp. 369-387, January, 2018. DOI: https://doi.org/10.1080/0952813X.2017.1421268.
BibTeX :
@article{misc-lab-177,
author = {Ferdi, Imene and Layeb, Abdesslem},
title = {A GRASP algorithm based new heuristic for the capacitated location routing problem},
journal = {Journal of Experimental & Theoretical Artificial Intelligence (JETAI)},
volume = {30},
number = {3},
issn = {1362-3079},
pages = {369--387},
publisher = {Taylor & Francis},
year = {2018},
month = {January},
doi = {10.1080/0952813X.2017.1421268},
url = {https://doi.org/10.1080/0952813X.2017.1421268},
keywords = {Optimisation problems, capacitated location-routing problem, constructive heuristics, GRASP, local search}
}
RIS :
TI  - A GRASP algorithm based new heuristic for the capacitated location routing problem
AU - I. Ferdi
AU - A. Layeb
PY - 2018
SN - 1362-3079
JO - Journal of Experimental & Theoretical Artificial Intelligence (JETAI)
VL - 30
IS - 3
SP - 369
EP - 387
PB - Taylor & Francis
AB - AbstractIn this paper, the capacitated location-routing problem (CLRP) is studied. CLRP is composed of two hard optimisation problems: the facility location problem and the vehicle routing problem. The objective of CLRP is to determine the best location of multiple depots with their vehicle routes such that the total cost of the solution is minimal. To solve this problem, we propose a greedy randomised adaptive search procedure. The proposed method is based on a new heuristic to construct a feasible CLRP solution, and then a local search-based simulated annealing is used as improvement phase. We have used a new technique to construct the clusters around the depots. To prove the effectiveness of our algorithm, several LRP instances are used. The results found are very encouraging.
KW - Optimisation problems
KW - capacitated location-routing problem
KW - constructive heuristics
KW - GRASP
KW - local search
DO - 10.1080/0952813X.2017.1421268
UR - https://doi.org/10.1080/0952813X.2017.1421268
ID - misc-lab-177
ER -