Probabilistic Fuzzy Approach to Evaluation of Logistics Service Effectiveness

• Autorzy: Katarzyna Rudnik , Iwona Pisz
• Języki publikacji: EN

Abstrakty

EN

Logistics service providers offer a whole or partial logistics business service over a certain time period. Between such companies, the effectiveness of specific logistics services can vary. Logistics service providers seek the effective performance of logistics service. The purpose of this paper is to present a new approach for the evaluation of logistics service effectiveness, along with a specific computer system implementing the proposed approach - a sophisticated inference system, an extension of the Mamdani probabilistic fuzzy system. The paper presents specific knowledge concerning the relationships between effectiveness indicators in the form of fuzzy rules which contain marginal and conditional probabilities of fuzzy events. An inference diagram is also shown. A family of Yager's parameterized t-norms is proposed as inference operators. It facilitates the optimization of system parameters and enables flexible adjustment of the system to empirical data. A case study was used to illustrate the new approach for the evaluation of logistics service effectiveness. The approach is demonstrated on logistics services in a logistics company. We deem the analysis of a probabilistic fuzzy knowledge base to be useful for the evaluation of effectiveness of logistics services in a logistics company over a given time period. (original abstract)

Słowa kluczowe

EN

Fuzzy systems; Logistics enterprise; Logistic services; Effectiveness evaluation

PL

Systemy rozmyte; Przedsiębiorstwo logistyczne; Usługi logistyczne; Ocena efektywności

• Czasopismo: Management and Production Engineering Review
• Rocznik: 2014
• Tom: 5
• Numer: nr 4
• Strony: 66--75

Twórcy

autor

Katarzyna Rudnik

• Opole University of Technology, Poland

autor

Iwona Pisz

• Opole University, Poland

Bibliografia

• [1] Christopher M., Logistics and supply chain management: creating value-adding networks, Pearson Education, Harlow, 2005.
• [2] Dyczkowska J., Marketing of logistics services [in Polish], Difin, Warsaw, 2014.
• [3] Krumwiede D.W., Sheu C., A model for reverse logistics entry by third-party provider, Omega 30, 325-333, 2002.
• [4] Mentzer J.T., Myers M.B., Cheung M.-S., Global market segmentation for logistics services, Industrial Marketing Management, 33, 15-20, 2004.
• [5] Pisz I., Łapuńka I., Conditions of logistics projects planning in transport-spedition- logistics sector on an example of oversize transportation, part 1 [in Polish], Logistics, CD-ROM, 2, 5134-5143, 2014.
• [6] Cui L., Hertz S., Networks and capabilities as characteristics of logistics firms, Industrial Marketing Management, 40, 1004-1011, 2011.
• [7] Rydzykowski W. [Ed.], Logistics services. Theory and practice [in Polish], LiM, Poznań, 2011.
• [8] Jeszka A.M., Logistics services sector in theory and practice [in Polish], Difin, Warsaw, 2013.
• [9] Kisperska-Moroń D., Krzyżaniak S. [Eds.], Logistics [in Polish], ILiM, Poznań, 2009.
• [10] Ying W., Dayong S., Multi-agent framework for third party logistics in E-commerce, Expert Systems with Applications, 29, 431-436, 2005.
• [11] Kasperek M., Szołtysek J., Logistics projects in outsourcing of logistics services [in Polish], Logistics, 6, 51-54, 2008.
• [12] Kasperek M., The agile method in logistics projects management [in Polish], Economic University of Katowice, Katowice, 2012.
• [13] Pisz I., Controlling of logistics project, Total Logistics Management, 4, 107-125, 2011.
• [14] Pisz I., Identification and risk assessment of logistics project [in:] Selected logistics problems and solutions, MONOGRAPH, Grzybowska K., Golińska P. [Eds.], Poznan House of Poznan University of Technology, Poznań, pp. 227-242, 2011.
• [15] Pisz I., Multi-criteria evaluation of the efficiency of logistics projects based on the Balanced Scorecard and fuzzy set theory [in Polish], Logistics, 5, 164-169, 2014.
• [16] Pisz I., Kolasa-Więcek A., Approach to the assessment of the efficiency of logistics projects using fuzzy inference systems [in Polish], [in:] The chosen issue of logistics in practice, Vol. 1, Lichota A., Majewska K. [Eds.], AGH, Krakow, pp. 281-294, 2013.
• [17] Twarog J., Logistics factors and indicators [in Polish], Library Logistics, Poznań 2005.
• [18] Najmi M., Kehoe D.F., The role of performance measurement systems in promoting quality development beyond ISO 9000, International Journal of Operations & Production Management, 1/2, 159-171, 2001.
• [19] Almeida R.J., Kaymak U., Probabilistic fuzzy systems in value-at-risk estimation, Intelligent Systems in Accounting, Finance and Management, 16, 49-70, 2009.
• [20] Tang M., Chen X., Hu W., Yu W., Generation of a probabilistic fuzzy rule base by learning from examples, Information Sciences, 217, 21-30, 2012.
• [21] Zadeh L.A., Fuzzy sets, Inform. Contr., 8, 338-353, 1965.
• [22] Zadeh L.A., Probability measures of fuzzy events, Journal of Mathematical Analysis and Applications, 23, 2, 421-427, 1968.
• [23] Rudnik K., Inference system with probabilistic fuzzy knowledge base: theory, concept and application [in Polish], Opole University of Technology, Opole 2013.
• [24] Walaszek-Babiszewska A., Construction of Fuzzy Models Using Probability Measures of Fuzzy Events, In Proc. 13th IEEE Internat. Conf. on Methods and Models in Automation and Robotics, MMAR 2007, Szczecin, Poland, pp. 661-666, 2007.
• [25] Walaszek-Babiszewska A., Fuzzy modeling in stochastic environment: theory, knowledge bases, examples, LAP Lambert Academic Publishing, 2011.
• [26] Kacprzyk J., Multi-stage fuzzy control [in Polish], WNT, Warszawa 2001.
• [27] Rudnik K., Walaszek-Babiszewska A., Probabilistic fuzzy knowledge-based system for managerial applications, Management and Production Engineering Review, March, 3, 1, 49-61, 2012.
• [28] Walaszek- Babiszewska A., Rudnik K., Stochastic-Fuzzy Knowledge-Based Approach to Temporal Data Modeling, Time Series Analysis, Modeling and Applications: A Computational Intelligence Perspective; W. Pedrycz, S.-M. Chen [Eds.], Springer-Verlag Berlin Heidelberg, pp. 97-118, 2013.
• [29] Mamdani E.H., Assilian S., An experiment in linguistic synthesis with a fuzzy logic controller, International Journal of Man-Machine Studies, 7, 1-13, 1975.

Identyfikatory

DOI

10.2478/mper-2014-0037