Forecasting the demand for transport services on the example of a selected logistic operator

Authors

DOI:

https://doi.org/10.5604/01.3001.0014.0210

Keywords:

multiple regression, forecasting, cross-docking

Abstract

The number of shipments is growing every year, and as a result, new transport companies arise. The increase in competition requires from entrepreneurs to apply solutions increasing the level of services provided in order to best satisfy the needs of the customers. In this aspect, minimizing the time of deliveries is extremely important, and it can be achieved, for example, by implementing the cross-docking method. It consists in consolidation of cargo from different shipment locations that is delivered in the same direction. The main feature of the above method is to keep the labor intensity of operations and the interference in the cargo to the minimum. The purpose of this article is to present a research on a logistic operator working based on a cross-docking warehouse with a capacity significantly lower than the average daily quantity of shipments handled. This requires both effective management of the available space and minimizing the time spent on manipulation activities. Therefore, it is important to know the expected number of parcels that are planned to be received and shipped on a given day in order to coordinate the work in the warehouse. It is possible to estimate it by using mathematical methods of forecasting. One of them - the multiple regression - is presented in this article. The calculations were made on the basis of collected empirical observations concerning orders for pallet spaces placed by customers. Such a forecast allows for improvement of the processes of planning and management of the possessed resources. It allows to adjust the number of warehouse workers or vehicles necessary for internal transport to the expected needs. Ultimately, it may translate into more efficient functioning not only of the surveyed branch, but also of the whole network.

References

BARTHOLDI J.J., GUE K.R., 2000, Reducing labor costs in an LTL cross-docking terminal, Operation Research. 48:6, 823-832.

BIELIŃSKA E., 2007, Prognozowanie ciągów czasowych. Wydawnictwo Politechniki Śląskiej.

BOZARTH C., HANDFIELD R., 2007, Wprowadzenie do zarządzania operacjami i łańcuchem dostaw, Helion, 440.

COMI A., BUTTARAZZI B., SCHIRALDI M., INNARELLA R., VARISCO M., TRAINI P., 2018. An advanced planner for urban freight delivering. Archives of Transport, 48(4), 27-40. DOI: https://doi.org/10.5604/01.3001.0012.8363.

DITTMANN P., 2000, Metody prognozowania sprzedaży w przedsiębiorstwie, Wydawnictwo Akademii Ekonomicznej.

DWI A., LEE C. K. M., RAJESH P., 2010, A review: Mathematical Modles for cross docking planning, International Journal of Engineering Business Management, 2, 47-54.

DWI A., LEE C. K. M., RAJESH P., 2014, vehicle scheduling and routing at a cross docking center for food supply chains, International Journal of Production Economics, 152, 29-41.

DYDKOWSKI G., 2018, The application of just distribution theories to financing integrated systems of regional and urban public transport, Scientific Journal of Silesian University of Technology. Series Transport 100, 23-33. DOI: https://doi.org/10.20858/sjsutst.2018.100.3.

ENDERER F., CONTARDO C., CONTRE-RAS I., 2017, Integrating dock-door assignment and vehicle routing with cross-docking, Computers & Operation Research, 88, 30-43.

HOSSEINI S., SHIRAZI M., KARIMI B., 2014, Cross-docking and milk run logistics in a consolidation network: A hybrid of harmony search and simulated annealing approach, Journal of Manufacturing Systems, 33:4, 597-577.

JACYNA-GOŁDA I, IZDEBSKI M., SZCZEPAŃSKI E., GOŁDA P., 2018. The assessment of supply chain effectiveness. Archives of Transport, 45(1), 43-52. DOI: https://doi.org/10.5604/01.3001.0012.0966.

KAWA A., 2017, Analiza rynku KEP w Polsce, GS1 Polska.

KESHTZARI M., NADERI B., MEHDIZADEH E., 2016, An improved mathematical model and a hybrid metaheuristic for truck scheduling in cross-dock problems, Computers & Industrial Engineering, 91, 197-204.

KOZIARKIEWICZ R., 2009, Słownik transportu i logistyki, C.H. Beck.

KUCUKOGLU I., OZTURK N., 2014, Simulated Annealing Approach for Transportation Problem of Cross-docking Network Design, Procedia - Social and Behavioral Sciences, 109, 1180-1184.

LADIER A.-L., ALPAN G., 2016, Cross-docking operatios: current research versus industry practice, Omega, 62, 145-162.

LADIER A-L., ALPAN G., 2016, Cross-docking operations: Current research versus industry practice, Omega 62, 145-162. DOI: https://doi.org/10.1016/j.omega.2015.09.006.

LENG K., SHI W., CHEN J., LV Z., 2015, Design of an I-Shaped Less-Than-Truckload Cross-Dock: A Simulation Experiment Study, International Journal of Bifurcation and Chaos, 25:14, 1540019.

LEWCZUK K., 2013, Wybrane aspekty projektowania terminali cross-dockingowych, Prace Naukowe Politechniki Warszawskiej, 97, 327-336.

MATTIAS J., TAMÁS M., CSABA K., 2017. Forecasting travel time reliability in urban road transport. Archives of Transport, 43(3), 53-67. DOI: https://doi.org/10.5604/01.3001.0010.4227.

MICHAŁOWSKA M. (red.), 2010, Efektywność transportu w teorii i praktyce, Uniwersytet Ekonomiczny w Katowicach, 76-80.

MOHAMMAD T. A., MOHSEN B., 2016., Differential evolution and Population-based simulated annealing for truck scheduling problem in multiple door cross-docking systems, Computers & Industrial Engineering, 96, 149-161.

MOUSAVI S. M., VAHDANI B., TAVAK-KOLI-MOGHADDAM R., 2014, Optimal Design of the cross-docking in distribution networks: heuristic solution approach, 27:4, 533-544.

NASSIEF W., CONTRERAS I., AS’AD R., 2016, A mixed-integer programming formulation and Lagrangean relaxation for the cross-dock door assignment problem, International Journal of Production Research, 54:2, 494-508. DOI: 10.1080/00207543.2014.1003664.

NASSIEF W., CONTRERAS I., JUAMARD B., 2018, A comparison of formulations and relaxations for cross-dock door assignment problems, Computers & Operation Research, 94, 76-88.

NIKOLOPOULOU A., REPOUSSIS P., TARANTILIS C., ZACHARIDIS E., 2017, Moving products between location pairs: cross-docking versus direct-shipping, European Journal of Operational Research 256 (3), 809-819. DOI: https://doi.org/10.1016/j.ejor.2016.06.053.

SOKOŁOWSKI A., 2016, Prognozowanie i analiza szeregów czasowych. Materiały szkoleniowe, Statsoft Polska.

SOLEIMANINANADEGANY A., HASSAN A., GALANKASHI M. R., 2017, Product allocation of warehousing and cross docking: a genetic algorithm approach, International Journal Services and Operations Management, 27:2, 239-260.

WOOYEON Y., EGBELU P.J., 2008, Scheduling of inbound and outbound trucks in cross docking systems with temporary storage, European Journal of Operational Research. 184, 377-396.

VINCENT F., JEWPANYA P., PERWIRA REDI A, 2016, Open vehicle routing problem with cross-docking, Computers & Industrial Engineering, 94, 6-17.

ZDUNEK P., 2017, Realizacja procesu dystrybucji i doskonalenie metody poolingu w oparciu o wykorzystanie cross-dockingu na przykładzie wybranego operatora logistycznego branży FMCG, Przedsiębiorczość i zarządzanie, vol. XVII (8), part II, 309-326.

Downloads

Published

2019-12-31

Issue

Section

Original articles

How to Cite

GRZELAK, M., BORUCKA, A., & BUCZYŃSKI, Z. (2019). Forecasting the demand for transport services on the example of a selected logistic operator. Archives of Transport, 52(4), 81-93. https://doi.org/10.5604/01.3001.0014.0210

Share

Most read articles by the same author(s)

Similar Articles

51-60 of 65

You may also start an advanced similarity search for this article.