Abstract—This paper addresses the resource control issue in goods distribution networks. Two types of actors—suppliers
and warehouses—are linked without topological restrictions.
The interconnection structure in the discussed class of logistic
networks forms a mesh-type topology. During the distribution process, the warehouses face external demands, not known a
priori. The flow of goods in the system is governed according to the networked order-up-to (NOUT) inventory management
policy implemented in a centralized manner. The balance between the customer service level and the holding cost poses a bi-objective optimization challenge. The novelty of this paper is
an application of the nondominated sorting genetic algorithm II
to adjust the NOUT policy to the logistic problem under consideration. Numerical studies performed for various
topologies and distribution structures have asserted the efficiency of the discussed method.
Index Terms—Logistic networks, genetic algorithms,
multi-objective optimization, uncertain demand, inventory management.
The authors are with the Institute of Information Technology, Lodz University of Technology, 90-924 Łódź, Poland (e-mail: przemyslaw.ignaciuk@p.lodz.pl, lukasz.wieczorek.1@edu.p.lodz.pl).
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Cite: Przemysław Ignaciuk and Łukasz Wieczorek, "Bi-objective Optimization of Logistic Networks with
Full-Connectivity Structure Using NSGA-II," International Journal of Modeling and Optimization vol. 9, no. 2, pp. 55-61, 2019.
