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Rozwiązywanie zagadnień decyzyjnych współczesnej logistyki : kryteria i metody. Część 2. Analiza decyzji

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Warianty tytułu
EN
Solving decision problems in contemporary logistics : evaluation criteria and methods Part 2. Decision analysis
Języki publikacji
PL
Abstrakty
PL
W pracy dokonano przeglądu zagadnień analizy decyzji występujących we współczesnej logistyce. Wykorzystano w tym celu najnowszą literaturę. Szczególną uwagę poświęcono metodom rozwiązywania zagadnień oraz kryteriom stosowanym do oceny rozwiązań. Przegląd ujawnił zróżnicowanie zagadnień i sposobów ich rozwiązywania. Pośród sposobów rozwiązywania dominują uniwersalne metody wielokryterialnej analizy decyzji. Poza nimi bywają również stosowane narzędzia wykorzystywane do rozwiązywania zagadnień programowania decyzji. Zróżnicowanie potrzeb oceny rozwiązań powoduje, że w tym celu są stosowane rozliczne kryteria o zróżnicowanym charakterze. Charakter metod analizy decyzji sprzyja stosowaniu kryteriów jakościowych. W przypadku zagadnień o specyficznym charakterze liczba zastosowanych kryteriów jakościowych może znacząco przekraczać liczbę kryteriów ilościowych. Najczęściej stosowane są zestawy liczące 4 lub więcej kryteriów.
EN
A literature survey of decision analysis problems in contemporary logistics is discussed in the paper. Special attention is drawn to methods applied while solving such problems and criteria utilized while evaluating possible problem solutions. It proves that there are diverse decision analysis problems that deal with logistics. Numerous approaches are applied to solve such problems. Universal approaches are utilized most often. Other approaches which are also suitable for solving decision programming problems are applied too. Diversity of actual needs results in application of different evaluation criteria while solving decision analysis problems in logistics. Solving typical decision analysis problems usually relies on the utilization of sets consisting of at least 4 criteria. Nature of decision analysis tools makes qualitative criteria more often applied than in the case of modelling decision programming problems. In some cases number of applied qualitative criteria may be even considerably larger than number of applied quantitative criteria.
Czasopismo
Rocznik
Tom
Strony
3085--3094, CD2
Opis fizyczny
Bibliogr. 30 poz.
Twórcy
autor
  • AGH Akademia Górniczo-Hutnicza w Krakowie, Wydział Zarządzania, 30-067 Kraków, ul. Gramatyka 10
autor
  • AGH Akademia Górniczo-Hutnicza w Krakowie, Wydział Zarządzania, 30-067 Kraków, ul. Gramatyka 10
Bibliografia
  • 1. Aggarwal R. Singh S. P., Chance constraint-based multi-objective stochastic model for supplier selection. International Journal of Advanced Manufacturing Technology 2015 [doi: 10.1007/s00170-015-6916-6].
  • 2. Aguezzoul A., Third-party logistics selection problem: A literature review on criteria and methods. Omega 2015, vol.49, pp.69-78.
  • 3. Ahi P., Searcy C., An analysis of metrics used to measure performance in green and sustainable supply chains. Journal of Cleaner Production 2015, vol.86, pp.360-377.
  • 4. Avelar-Sosa L., García-Alcaraz J.L., Vergara-Villegas O.O., Maldonado-Macías A.A., AlorHernández G., Impact of traditional and international logistic policies in supply chain performance. International Journal of Advanced Manufacturing Technology 2015, vol.76, pp.913-925.
  • 5. Arabzad S.M., Ghorbani M., Razmi J., Shirouyehzad H., Employing fuzzy TOPSIS and SWOT for supplier selection and order allocation problem. International Journal Advanced Manufacturing Technology 2015, vol.76, pp.803-818.
  • 6. Basu R.J., Bai R., Palaniappan PL.K., A strategic approach to improve sustainability in transportation service procurement. Transportation Research Part E 2015, vol.74, pp.152-168.
  • 7. Bienstock C.C., Royne M.B., Sherrell D., Stafford T.F., An expanded model of logistics service quality: Incorporating logistics information technology. International Journal of Production Economics 2008, vol.113, pp.205-222.
  • 8. Blyde J., Molina D., Logistic infrastructure and the international location of fragmented production. Journal of International Economics 2015, vol.95, pp.319-332.
  • 9. Chou J.-S., Ongkowijoyo C.S., Reliability-based decision making for selection of ready-mix concrete supply using stochastic superiority and inferiority ranking method. Reliability Engineering and System Safety 2015, vol.137, pp.29-39.
  • 10. Dos Santos S.F., Brandi H.S., Model framework to construct a single aggregate sustainability indicator: an application to the biodiesel supply chain. Clean Technologies and Environmental Policy 2015 [doi: 10.1007/s10098-015-0919-8].
  • 11. Ge H., Gray R., Nolan J., Agricultural supply chain optimization and complexity: A comparison of analytic vs simulated solutions and policies. International Journal of Production Economics 2015, vol.159, pp.208-220.
  • 12. Govindan K., Azevedo S. G., Carvalho H., Cruz-Machado V., Lean, green and resilient practices influence on supply chain performance: interpretive structural modeling approach. International Journal of Environmental Science and Technology 2015, vol.12, pp.15-34.
  • 13. Ha O., Choi B.-L., Kim Y., Kim B., Lee K.-D., Development of indicators of freight stations for digital convergence. Cluster Computing 2015, vol.18, pp.269-278.
  • 14. Hashemi S.H., Karimi A., Tavana M., An integrated green supplier selection approach with analytic network process and improved Grey relational analysis. International Journal of Production Economics 2015, vol.159, pp.178-191.
  • 15. Henn S., Order batching and sequencing for the minimization of the total tardiness in picker-to-part warehouses. Flexible Services and Manufacturing Journal 2015, vol.27, pp.86-114.
  • 16. Hsueh J.-T., Lin C.-Y., Constructing a network model to rank the optimal strategy for implementing the sorting process in reverse logistics: case study of photovoltaic industry. Clean Technologies and Environmental Policy 2015, vol.17, pp.155-174.
  • 17. Jaberidoost M., Olfat L., Hosseini A., Kebriaeezadeh A., Abdollahi M., Alaeddini M., Dinarvand R., Pharmaceutical supply chain risk assessment in Iran using analytic hierarchy process (AHP) and simple additive weighting (SAW) methods. Journal of Pharmaceutical Policy and Practice 2015, vol.8(9), pp.1-10.
  • 18. Karande P., Chakraborty S., Supplier Selection Using Weighted Utility Additive Method. Journal of the Institution of Engineers (India): Series C 2015, [10.1007/s40032-015-0177-x].
  • 19. Lam H.Y., Choy K.L., Ho G,T.S., Cheng S.W.Y., Lee C.K.M., A knowledge-based logistics operations planning system for mitigating risk in warehouse order fulfilment. Int. J. Production Economics 2015 [http://dx.doi.org/10.1016/j.ijpe.2015.01.005].
  • 20. Lee J., Cho H., Kim Y.S., Assessing business impacts of agility criterion and order allocation strategy in multi-criteria supplier selection. Expert Systems with Applications 2015, vol.42, pp.1136-1148.
  • 21. Mangla S.K., Kumar P., Barua M.K., Flexible Decision Modeling for Evaluating the Risks in Green Supply Chain Using Fuzzy AHP and IRP Methodologies. Global Journal of Flexible Systems Management 2015, vol.16(1), pp.19-35.
  • 22. Moral-Pajares E., Mozas-Moral A., Bernal-Jurado E., Medina-Viruel M.J., Efficiency and exports: Evidence from Southern European companies. Journal of Business Research 2015 [http://dx.doi.org/10.1016/j.jbusres.2015.01.042].
  • 23. Munapo E., Lesaoana M., Nyamugure P., Kumar S., A transportation branch and bound algorithm for solving the generalized assignment problem. International Journal of System Assurance Engineering and Management 2015 [doi: 10.1007/s13198-015-0343-9].
  • 24. Olivos P.C., Carrasco F.O., Flores J.L.M., Moreno Y.M., Nava G.L., Modelo de gestión logística para pequeñas y medianas empresas en México. Contaduría y Administración 2015, vol.60(1), pp.181-203.
  • 25. Paul S.K., Supplier selection for managing supply risks in supply chain: a fuzzy approach. International Journal of Advanced Manufacturing Technology 2015 [10.1007/s00170-015-6867-y].
  • 26. Pitchipoo P., Venkumar P., Rajakarunakaran S., Grey decision model for supplier evaluation and selection in process industry: a comparative perspective. International Journal of Advanced Manufacturing Technology 2015, vol.76, pp.2059-2069.
  • 27. Simić D., Svirčević V., Simić S., A hybrid evolutionary model for supplier assessment and selection in inbound logistics. Journal of Applied Logic 2015, vol.13, pp.138-147.
  • 28. Stoll J., Kopf R., Schneider J., Lanza G., Criticality analysis of spare parts management: a multicriteria classification regarding a cross-plant central warehouse strategy. Production Engineering. Research and Development 2015, vol.9, pp.225-235.
  • 29. Wu Z., Xu J., Xu Z., A multiple attribute group decision making framework for the evaluation of lean practices at logistics distribution centers. Annals of Operational Research 2015 [doi: 10.1007/s10479-015-1788-6].
  • 30. Yu C., Wong T.N., A product bundle determination model for multi-product supplier selection. Journal of Intelligent Manufacturing 2015, vol.26, pp.369-385.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-39335f31-2b78-4117-a5fc-7ef1685c9986
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