Authors:
Seyed Farid Ghannadpour
and
Mohsen Hooshfar
Affiliation:
MAPNA Co., Iran, Islamic Republic of
Keyword(s):
Vehicle Routing Problem, Multi-Objective Optimization, Fuzzy Time Windows, Dynamic Request.
Related
Ontology
Subjects/Areas/Topics:
Applications
;
Artificial Intelligence
;
Industrial Engineering
;
Knowledge Discovery and Information Retrieval
;
Knowledge-Based Systems
;
Methodologies and Technologies
;
Operational Research
;
Optimization
;
OR in Transportation
;
Pattern Recognition
;
Routing
;
Scheduling
;
Software Engineering
;
Symbolic Systems
Abstract:
This paper studies the multi-objective dynamic vehicle routing and scheduling problem by using an evolutionary method. In this model, all data and information required to the routing process are not known before planning and they revealed dynamically during the routing process and the execution of the routes. Moreover, the model tries to characterize the customers’ satisfaction and the service level issues by applying the concept of fuzzy time windows. The proposed model is considered as a multi-objective problem where the overall travelling distance, fleet size and waiting time imposed on vehicles are minimized and the customers’ satisfaction or the service level of the supplier to customers is maximized. To solve this multi-objective model, an evolutionary algorithm is developed to obtain the Pareto solutions and its performance is analyzed on various test problems in the literature. The computational experiments on data sets represent the efficiency and effectiveness of the propos
ed approach.
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