Authors:
S. Kande
1
;
C. Prins
2
;
L. Belgacem
3
and
B. Redon
3
Affiliations:
1
University of Technology of Troyes and FuturMaster, France
;
2
University of Technology of Troyes, France
;
3
FuturMaster, France
Keyword(s):
Distribution network, Multi-Start Iterated Local Search, Local Search, Lot-sizing, Metaheuristic, Multi-echelon inventory, Multi-sourcing, Perishable product, Supply planning, Transport capacity, Variable neighborhood descent.
Related
Ontology
Subjects/Areas/Topics:
Applications
;
e-Business
;
Enterprise Information Systems
;
Industrial Engineering
;
Logistics
;
Methodologies and Technologies
;
Operational Research
;
Supply Chain Management
Abstract:
This article presents a planning problem in a distribution network incorporating two levels inventory management of perishable products, lot-sizing, multi-sourcing and transport capacity with a homogeneous fleet of vehicles. A mixed integer linear programming (MILP) and a greedy heuristic were developed to solve this real planning problem. There are some instances for which the solver cannot give a good lower bound within the limited time and for other instances it takes a lot of time to solve MILP. The greedy heuristic is an alternative to the mixed integer linear program to quickly solve some large instances taking into account original and difficult constraints. For some instances the gap between the solutions of the solver (MILP) and the heuristic becomes quite significant. A multi-start iterated local search (MS-ILS), using the variable neighborhood descent (VND) and a greedy randomized heuristic, has been implemented. It has been included in an APS
(Advanced Planning System) an
d compared with an exact resolution of the MILP. The instances are derived from actual data or built using a random generator of instances to have wider diversity for computational evaluation. The MS-ILS significantly improves the quality of solutions.
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