Paper Review: The Multi-criteria Decision Support in Choosing the Efficient Location of Warehouses in the Logistic Network

review

English

Paper Review of the Conference Transbaltica 2017 Conference. Abstract of the paper: The warehouse facilities location is a complex multi-objective decision problem. In order to determine the location one can use a different mathematical models that describe the location of these objects according to the accepted constraints and criterion functions. This paper presents the warehouses location in the logistic network. The logistic network consists of suppliers, potentially warehouses with the known location and recipients. Selection of warehouses location depends on the criterion functions and constraints which are defined in the mathematical location model. The variety of constraints that must be considered e.g. the production capacity of suppliers, buyers, the storage capacity makes it difficult to decide on the final location of these objects. The warehouse location problem in the logistics network is multi-criteria optimization problem that depends on quantitative and qualitative criteria. In general, the optimization criteria takes the form: minimal storage costs, transition costs of the cargo through warehouse facilities, the cost of cargo transport to the warehouse facility, etc. The article points out the benefits of using a genetic algorithm to efficiently solve the multi-criteria problem of warehouses location in the logistics network. The article presents some aspects concerning the application of the modified genetic algorithm for effective solutions of complex multi-criteria warehouses location problem in the logistic network. The complexity of the warehouse location problem dictated by the diversity of constraints and decision variables (e.g. the type of binary decision variables and the real type), the search for the location of many warehouse facilities at the same time, multi-criteria aspects of the problem imposes the need for the application of an appropriate optimization algorithm adequately to the presented location problem.

multi-criteria warehouses location problem; genetic algorithm; effectiveness of location selection

VENKRBEC, V.

27. 1. 2017

Vilnius Gediminas Technical University

Vilnius, Lithuania

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