Authors:
Yun He
1
;
Cyril Briand
1
and
Nicolas Jozefowiez
2
Affiliations:
1
CNRS, LAAS, Univ. de Toulouse and UPS, France
;
2
CNRS, LAAS, Univ. de Toulouse and INSA, France
Keyword(s):
Inventory Routing Problem, Energy Minimization, Mixed Integer Linear Programming.
Related
Ontology
Subjects/Areas/Topics:
Applications
;
e-Business
;
Energy and Environment
;
Enterprise Information Systems
;
Logistics
;
Operational Research
;
Pattern Recognition
;
Routing
;
Software Engineering
Abstract:
In this paper, we present a new mass-flow based Mixed Integer Linear Programming (MILP) formulation for
the Inventory Routing Problem (IRP) with explicit energy consumption. The problem is based on a multi-period
single-vehicle IRP with one depot and several customers. Instead of minimizing the distance or inventory
cost, the problem takes energy minimization as an objective. In this formulation, flow variables describing
the transported mass serve as a link between the inventory control and the energy estimation. Based on physical
laws of motion, a new energy estimation model is proposed using parameters like vehicle speed, average
acceleration rate and number of stops. The solution process contains two phases with different objectives: one
with inventory and transportation cost minimization as in traditional IRP, the other with energy minimization.
Using benchmark instances for inventory routing with parameters for energy estimation, experiments have
been conducted. Finall
y, the results of these two solution phases are compared to analyse the influence of
energy consumption to the inventory routing systems.
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