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Spatial Modeling In Logistics Decision-Making Processes. Identifying The Optimal Location For A Single Central Warehouse

Author

Listed:
  • Tartavulea Ramona Iulia

    (Academia de Studii Economice Bucuresti, Facultatea de Relatii Economice Internationale)

  • Belu Mihaela Gabriela

    (Academia de Studii Economice Bucuresti, Facultatea de Relatii Economice Internationale)

  • Dieaconescu Vlad Constantin

    (Polytechnic University of Bucharest, Computer Science Faculty)

Abstract

In the context of the EU single market formation it was observed a trend of giving up local deposits in favor of central regional warehouses. Another factor favoring centralization of storage is the economic crisis that has forced the need for efficient activity by making decisions on reducing costs. The first part of this paper focuses on literature review and presentation of the most important decision-making models developed in the field of logistics. Several models were selected and analyzed in detail to build a modern research methodology, based on precise mathematical calculations. In the decision making process of selecting an optimal location for a central warehouse, we used a series of mathematical models to identify the exact geographical position, which induces minimal cost for transportation to consumption points. In the second part of the paper, the article aims to identify the optimal location for a central warehouse in Romania. In this methodology, we chose 100 cities in Romania, positioned throughout the country and characterized as input by three sizes: latitude, longitude and population size. Latitude and longitude were used for graphical representation of the space considered (Romania) by individual points (cities), and the population was used as approximation of the demand for generic products. We applied a mathematical model in order to calculate the gravitational center using an excel spreadsheet. Each step in applying the model is explained in detail in the paper. The results of the research indicate the optimal location (characterized by its latitude: 45.469408 N and longitude: 25.630817 E) for placing a central warehouse that can supply the 100 cities with minimal transportation costs. Were also calculated the distances between the optimal location and the 100 cities and then identified 10 cities, the closest to our optimal location (Sinaia, Sacele, Brasov, Campina, Campulung, Ploiesti, Fagaras, Pitesti, Mierucurea-Ciuc, Odorheiu Secuiesc). Any of these cities can be chosen as location to build a central warehouse in Romania, because they represent a relatively good approximation for the gravitational center identified in the model applied.

Suggested Citation

  • Tartavulea Ramona Iulia & Belu Mihaela Gabriela & Dieaconescu Vlad Constantin, 2011. "Spatial Modeling In Logistics Decision-Making Processes. Identifying The Optimal Location For A Single Central Warehouse," Annals of Faculty of Economics, University of Oradea, Faculty of Economics, vol. 1(1), pages 137-143, July.
    • Handle: RePEc:ora:journl:v:1:y:2011:i:1:p:137-143
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    File URL: http://anale.steconomiceuoradea.ro/volume/2011/n1/083.pdf
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    References listed on IDEAS

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    1. P T Harker, 1988. "Dispersed Spatial Price Equilibrium," Environment and Planning A, , vol. 20(3), pages 353-368, March.
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    Cited by:

    1. Ramona Iulia ?ar?avulea (Dieaconescu) & Mihaela Gabriela Belu & Dorel Mihai Paraschiv & Ioan Popa, 2016. "Spatial Model for Determining the Optimum Placement of Logistics Centers in a Predefined Economic Area," The AMFITEATRU ECONOMIC journal, Academy of Economic Studies - Bucharest, Romania, vol. 18(43), pages 707-707, August.

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    More about this item

    Keywords

    logistics; decision making process; optimal location; warehouse; spatial modeling;
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • R31 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location - - - Housing Supply and Markets

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