Implementation of Optimization Methods in the Selected Areas of Production Logistics

• Autorzy: Petr Suchánek , Robert Bucki , Azra Korjenic
• Języki publikacji: EN

Abstrakty

EN

The contemporary business environment is constantly putting pressure on increasing efficiency in all areas of modern society. One of the key areas is undoubtedly production which is affected mainly by the dynamic development of modern technologies. However, it must be emphasized that production issues are not treated as a set of individual machines but as a system which is affected by the number of elements exerting both positive and negative influences on its course. These elements can be placed in the area of production logistics along with assigned production equipment, the human factor, methods of manipulation with materials and intermediates, storage, etc. Production logistics should be treated as a complex integrated system consisting of the predefined subsystems containing sets of related activities which are strictly categorized. Defining control rules of the individual subsystems appropriately results in increased efficiency of the entire system. In order to achieve the maximum possible efficiency of the entire system it is always necessary to optimize each subsystem which operates within its framework. Currently, simulation is used increasingly to support the optimization tasks and processes in all types of systems. The efficiency increases significantly when simulation tools become an inseparable layer parallel to the implemented control system. (original abstract)

Słowa kluczowe

EN

Logistics; Production logistics; Optimalization; Logistic management

PL

Logistyka; Logistyka produkcji; Optymalizacja; Zarządzanie logistyczne

• Czasopismo: Forum Scientiae Oeconomia
• Rocznik: 2015
• Tom: 3
• Numer: nr 2 Logistics Management
• Strony: 65--79

Twórcy

autor

Petr Suchánek

• Silesian University in Opava, Czech Republic

autor

Robert Bucki

• University of Dąbrowa Górnicza, Poland

autor

Azra Korjenic

• Vienna University of Technology, Austria

Bibliografia

• 1. Bucki, R., Suchánek, P. (2012), The method of logistic optimization. E-commerce, Journal of Universal Computer Science, Vol. 18, No. 10, pp. 1238-1258.
• 2. Černý, J. (2007), Logistika pro štíhlý podnik, IT SYSTEMS, No. 7-8.
• 3. Červeňan, Š., Sakál, P. (2002), Environmentálne aspekty logistiky, Slovenské centrum strategických studií, available at: http://www.scss.sk/eommlspj/_ data/VEGA 2002-2004/RIESITELIA/CERVENAN STEFAN/AFD Cervenan Sakal Zvolen 2003 Enviro - Logistika.pdf.
• 4. Chen, Y., Lin, F., Bi, N. (2006), The modeling analysis and optimization of production logistics in the discrete manufacturing enterprise based on multi-agent. Proceedings of the 13th International Conference on Industrial Engineering and Engineering Management, Vol. 1., No. 5, pp. 2185-2189.
• 5. Cheng, D., Podolsky, S. (1993), Just in time manufacturing: an introduction. Springer.
• 6. Chramcov, B., Balate, J. (2009), Model-building for time series of heat demand. Annals of DAAAM for 2009 & Proceedings of the 20th International DAAAM symposium, Vol. 20, pp. 195-196.
• 7. Christopher, M. (2011), Logistics and supply chain management. FT Press, New Jersey.
• 8. Dotoli, M., Fanti, M.P., Mangini, A.M., Tempone, G. (2005), Fuzzy multi-objective optimization for network design of logistic and production systems, ETFA 2005: 10th IEEE International Conference on Emerging Technologies and Factory Automation, Vol. 1, pts 1 and 2, 2005, pp. 475-482.
• 9. Factory Magazine (1988), Poka-Yoke: Improving product quality by preventing defects. Productivity Press.
• 10. Giribone, P., Revetria, R., Oliva, F., Schenone, M., Nikolova, E.N., Peneva, G.C. (2007), Integrate clustering and mathematical programming for supporting reverse logistics optimization: Methodology and case study. Proceedings of the 6th WSEAS International Conference on System Science and Simulation. Book Series: Electrical and Computer Engineering, pp. 30-37.
• 11. Hay, E.J., Zonderman, J. (1988), Just in time manufacturing: How the JIT system can decrease costs. Increase Productivity and Enhance Quality, Wiley.
• 12. Hirano, H. (1988), JIT factory revolution. Productivity Press.
• 13. Hsui, Ch., Tsai, C.Y., Lee, T.Y. (2010), Neural network to develop sizing systems for production and logistics via technology innovation in Taiwan. Proceedings of 10th WSEAS International Conference on Applied Informatics and Communications. Book Series: International Conference on Applied Informatics and Communications-International Conference on Biomedical Electronics and Biomedical Informatics, pp. 421-424.
• 14. Karageorgos, A., Mehandjiev, N., Weichhart, G., Hammerle, A. (2003), Agent-based optimization of logistics and production planning. Engineering Applications of Artificial Intelligence, Vol. 16, No. 4, pp. 335-348.
• 15. Kofjac, D., Kljajic, M. (2008), Furniture production optimization with visual simulation and genetic algorithms. Proceedings of 8th WSEAS International Conference on Simulation, Modeling and Optimization. Book Series: Mathematics and Computers in Science and Engineering, pp. 53-58.
• 16. Macias, E.J., De La Parte, M.P. (2004), Simulation and optimization of logistic and production systems using discrete and continuous petri nets. Simulation-transactions of the Society for Modeling and Simulation International. Vol. 80, No. 3, pp. 143-152.
• 17. Miller, A. (2009), Kritéria a efekty prostorového uspořádání výrobních systémů svoč - fst 2009, Západočeská univerzita v Plzni, available at: http://old.fst.zcu.cz/_files_web_FST/_SP_FST(SVOC)/_2009/_sbornik/PapersPdf/Ing/Miller_Antonin.pdf.
• 18. Němec, F. (2002), Výrobní logistika pro economy. Slezská univerzita. Obchodně podnikatelská fakulta, Karviná.
• 19. Olšovská, R., Butorová, P. (2008), Ekologická logistika a možnosti optimalizace nákladů spojených s ochranou životního prostředí, VVŠ PV ve Vyškově, available at: http://www.enviweb.cz/clanek/ems/48097/ekologicka-logistika-a-moznosti-optimalizace-nakladu-spojenych-s-ochranou-zivotniho-prostredi.
• 20. PPDT Productivity Press Development Team (1996), Quick changeover for operators. Shopfloor Series. Productivity Press.
• 21. Reis, C., Paiva, L., Moutinho, J. (2010), Genetic algorithms and sensitivity analysis in production planning optimization. Proceedings of 10th WSEAS International Conference on Applied Informatics and Communications. Book Series: International Conference on Applied Informatics and Communications-International Conference on Biomedical Electronics and Biomedical Informatics, pp. 246-251.
• 22. Řepa, V. (2006), Podnikové procesy. Procesní řízení a modelování. Grada Publishing, Praha.
• 23. Shapiro, J.F. (2006), Modeling the supply chain. South-Western College Pub.
• 24. Škapa, R. (2002), Skrytý potenciál reverzní logistiky. Logistika, Praha.
• 25. Šperka, R., Spišák, M., Slaninová, K. (2013), Control loop model of virtual company in BPM simulation. Soft Computing Models in Industrial and Environmental Applications, Vol. 188, pp. 515-524.
• 26. Suchánek, P. (2011), Business intelligence - the standard tool of a modern company. Proceedings of the 6th International Scientific Symposium on Business Administration: Global Economic Crisis and Changes: Restructuring Business System: Strategic Perspectives for Local, National and Global Actors, pp. 123-132.
• 27. Suchánek, P. (2012), E-commerce - Elektronické podnikání a koncepce elektronického obchodování. Ekopress, Praha.
• 28. Vymětal, D. (2009), Value chain and process models: is the gap between them real?. Proceedings of Distance Learning, Simulation and Communication, pp. 198-205.
• 29. Wooldridge, M. (2009), An introduction to multi agent systems. Wiley.
• 30. Zoghlami, N., Hammadi, S. (2007), Organization and optimization of distributed logistics: estimation and patrolling approach based on multi-agent system. Proceedings of the 11th WSEAS I nternational Conference on Systems. Vol. 2: Systems Theory and Applications, Book Series: Electrical and Computer Engineering, pp. 461-466.