Authors:
Hadhami Kaabi
1
and
Khaled Jabeur
2
Affiliations:
1
Institut Supérieur de Gestion, Tunisia
;
2
Institut Supérieur de Commerce et de Comptabilité, Tunisia
Keyword(s):
Multi-compartment, Vehicle Routing, Time Windows, Profit, Genetic Algorithm, Iterated Local Search.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Computational Intelligence
;
Evolutionary Computing
;
Genetic Algorithms
;
Industrial Engineering
;
Informatics in Control, Automation and Robotics
;
Intelligent Control Systems and Optimization
;
Optimization Algorithms
;
Production Planning, Scheduling and Control
;
Soft Computing
;
Supply Chain and Logistics Engineering
Abstract:
This paper presents a new variant of the well-known vehicle routing problem with time windows (VRPTW).
More precisely, this paper addresses a multi-compartment vehicle routing problem with time windows and
profit (MCVRPTW with profit). The aim of this problem is to serve a set of customers by using a set of
vehicles with multiple compartments, under a minimum traveling cost. The vehicles, starting and ending at
the depot, have a limited capacity and each compartment is dedicated to one product. A customer is served
only within a given time windows and, when it is visited a profit is collected (i.e. a profit not low than a
preset profit bound). To solve this problem, an hybrid approach combining the genetic algorithm (GA) and the
iterated local search (ILS) is used.