Paper Info
Title
Multi-objective genetic algorithm in green just-in-time logistics
Abstract
This paper addresses a mixed-integer linear programming model by integrating just-in-time delivery along with green objectives in a logistics network. Multi-objective genetic algorithm optimization has been applied in order to minimize the number of delivery and lead-time as well as environmental impact of logistic network. This evolutionary based algorithm incorporates non-dominated sorting genetic algorithm, so as to allow heuristic for parallel optimization of the objective functions. Computational results demonstrate efficiency of the proposed model for minimizing the objective functions. Finally, the conclusion and some areas of further research are proposed.
Year
DOI
Venue
2014
10.1109/IEEM.2014.7058836
Industrial Engineering and Engineering Management
Keywords
Field
DocType
environmental factors,genetic algorithms,integer programming,just-in-time,linear programming,logistics,environmental impact,evolutionary based algorithm,green just-in-time logistics,green objectives,just-in-time delivery,lead time,logistic network,logistics network,mixed integer linear programming model,multiobjective genetic algorithm optimization,nondominated sorting genetic algorithm,parallel optimization,Green supply chain,NSGA II,multi objective optimization
Heuristic,Mathematical optimization,Parallel optimization,Genetic algorithm optimization,Meta-optimization,Multi-objective optimization,Sorting,Linear programming,Engineering,Operations management,Genetic algorithm
Conference
ISSN
Citations 
PageRank 
2157-3611
1
0.38
References 
Authors
4
3
Name
Order
Citations
PageRank
Ashkan Memari1262.77
Abdul Rahman Bin Abdul Rahim210.38
Robiah Binti Ahmad3132.09