DocumentCode :
3585946
Title :
A solution for multi-objective commodity vehicle routing problem by NSGA-II
Author :
Shamshirband, Shahaboddin ; Shojafar, Mohammad ; Hosseinabadi, Ali A. R. ; Abraham, Ajith
Author_Institution :
Dept. of Comput. Syst. & Technol., Univ. of Malaya, Kuala Lumpur, Malaysia
fYear :
2014
Firstpage :
12
Lastpage :
17
Abstract :
Vehicle routing is considered the basic issue in distribution management. In real-world problems, customer demand for some commodities increases on special situations. On the one hand, one of the factors that are very important for customers is the timely delivery of the demanded commodities. In this research, customers had several different kinds of demands. Therefore, a new routing model was introduced in the form of integer linear programming by combining the concepts of time windows and multiple demands and by considering the two contradictory goals of minimizing travel cost and maximizing demand coverage. Moreover, two approaches were designed for the problem-solving model based on the NSGA-II algorithm with diversification of the mutation operator structure. The two criteria of spread and coverage of non-dominated solutions were used to compare algorithms. Study of some typical created problems indicated the validity of the model and the computational efficiency of the proposed algorithm. The proposed algorithm could increase the criterion of solution spread by about 10%, and increased the number of obtained solutions on the Pareto border compared to other algorithms, which indicated its high efficiency.
Keywords :
Pareto optimisation; genetic algorithms; integer programming; linear programming; minimisation; sorting; vehicle routing; NSGA-II algorithm; Pareto border; customer demands; demand coverage maximization; distribution management; integer linear programming; multiobjective commodity vehicle routing problem; mutation operator structure; nondominated sorting genetic algorithm-II; problem-solving model; time windows; travel cost minimization; Algorithm design and analysis; Pareto optimization; Routing; Sociology; Vehicle routing; Vehicles; Pareto-optimal solutions; Vehicle routing problem; multi-objective; non-dominated sorting genetic algorithm-II (NSGA-II); timewindows;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Hybrid Intelligent Systems (HIS), 2014 14th International Conference on
Print_ISBN :
978-1-4799-7632-4
Type :
conf
DOI :
10.1109/HIS.2014.7086201
Filename :
7086201
Link To Document :
بازگشت