Application of fuzzy sets to planning of chain delivery supplies

Katarzyna Topolska, Mariusz Topolski


The article shows supply planning model with using soft methods of calculation. Supplies prediction is rather stochastic process than deterministic one. The changing market demand influences by different factors which can be difficult to predict cause big problems in prognostic procedures. Applying solution based on fuzzy set cause that conclusions based on uncertain or imprecision data gives better solutions than statistics method (in the meaning of proper prognosis). In this work it has been shown sequential model of supply planning, which takes into account some predetermined trajectory of former observations. Very important element of such a model is sensitivity on season changes and big adaptation to new emerged predetermined trend changes. In the following part of the work it has been shown the results of investigations based on experimental data, which tried out efficacy of proposed prognosis (together with estimation error).


supply planning model; soft methods of calculation

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Kurzyński M., Benchmark of Approaches to Sequential Diagnosis, artificial neural networks in medicine, Springer Verlag, Berlin–Heidelberg–New York 1998.

Kurzyński M., Sequential Classification Via Fuzzy Relations, [in:] Artificial intelligence and soft Computing (iCais2006), 8th International Conference, Zakopane, Poland, June 2006, Kraków 2006.

Łęski J., Zbiory rozmyte i ich interpretacja. Wprowadzenie do teorii możliwości, Wydawnictwa Politechniki Śląskiej, Gliwice 2001.

Rutkowska D., Piliński M., Rutkowski L., Sieci neuronowe, algorytmy genetyczne i systemy rozmyte, Wydawnictwo Naukowe PWN, Łódź–Warszawa 1999.

Topolski M., Komputerowe algorytmy rozpoznawania sekwencyjnego z modelem łączącym teorię ewidencji matematycznej z teorią zbiorów rozmytych, praca doktorska, PRE 1/07, Politechnika Wrocławska, Wrocław 2007.

Żołnierek A., The pat tern recognition alghorithm for controlled Markov chains with learning and additional classifier, [in:] Advanced simulation of system. Procedings of the 25th International Autumn Colloquium, Sv. Hostyn, september 8-10, 2003, ed. Stefan J., Praha 2003.


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