Authors:
Seyed Farid Ghannadpour
and
Mohsen Hooshfar
Affiliation:
MAPNA Co., Iran, Islamic Republic of
Keyword(s):
Vehicle Routing Problem, Fuel Consumption, Customers' Priority, Multi-Objective, Evolutionary Algorithm.
Related
Ontology
Subjects/Areas/Topics:
Applications
;
Artificial Intelligence
;
e-Business
;
Enterprise Information Systems
;
Industrial Engineering
;
Knowledge Discovery and Information Retrieval
;
Knowledge-Based Systems
;
Linear Programming
;
Logistics
;
Mathematical Modeling
;
Methodologies and Technologies
;
Operational Research
;
Optimization
;
OR in Transportation
;
Pattern Recognition
;
Routing
;
Scheduling
;
Software Engineering
;
Supply Chain Management
;
Symbolic Systems
Abstract:
Transportation often represents the most important single element in logistics costs and its reduction and finding the best routes that a vehicle should follow through a network is an important decision. the energy cost is a significant part of total transportation cost and it is important to improve the operational efficiency by decreasing energy consumption. Unlike most of the studies trying to minimize the cost by minimizing overall travelling distance, the energy minimizing which meets the latest requirements of green logistics, is considered in this paper. the customers' priority for servicing is considered as well. Besides, the model is interpreted as multi-objective optimization where, the energy consumed and the total fleet are minimized and the total satisfaction rates of customers is maximized. A new solution based on the evolutionary algorithm is proposed and its performance is compared with the CPLEX Solver. Results illustrate the efficiency and effectiveness of proposed
approach.
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