Routing of hazardous materials using a population learning algorithm

• Autorzy: Barbucha D.

Warianty tytułu

PL

Wyznaczanie tras przewozu materiałów niebezpiecznych z wykorzystaniem algorytmu uczenia populacji

• Konferencja: European Safety and Reliability Conference, ESREL 2005 (16 ; 27-30.06.2005 ; Gdynia-Sopot-Gdańsk)
• Języki publikacji: EN

Abstrakty

EN

The hazardous materials transportation covers a large part of economic activities in the industrial countries. Amount of hazardous materials transported over the world grows systematically. Although hazardous materials accidents are rare events, their impact can be severe for the human and natural environment. This feature of hazardous materials transportation adds a special concern in the decision-making process of hazardous materials transportation. The problem of optimal routing of hazardous materials is described and formally defined in the paper as an extension of classical vehicle routing problem by taking into account minimisation of the risk. A new heuristic algorithm for solving the routing of hazardous materials problem based on evolution of population is presented in the paper. It is also evaluated using benchmark data sets and then solutions generated by the algorithm are compared with optimal ones.

PL

W pracy został opisany i formalnie zdefiniowany problem optymalnego wyznaczenia tras przewozu materiałów niebezpiecznych, jako rozszerzenie klasycznego problemu wyznaczenia tras pojazdów przez uwzględnienie ryzyka związanego z transportem. Dla omawianego problemu zaproponowano nowy algorytm heurystyczny oparty na ewolucji populacji. Został on poddany eksperymentom obliczeniowym z użyciem danych benchmarkowych, a następnie na podstawie wyników otrzymanych za pomocą tego algorytmu dokonano jego oceny.

Słowa kluczowe

PL

przewóz materiałów niebezpiecznych; trasa przewozu; algorytm uczenia populacji; optymalizacja

• Wydawca: Warsaw University of Technology, Faculty of Transport
• Czasopismo: Archives of Transport
• Rocznik: 2005
• Tom: Vol. 17, iss.3-4
• Strony: 11--24
• Opis fizyczny: Bibliogr. 13 poz., tab.

Twórcy

autor

Barbucha D.

• Maritime University of Gdynia, Dept. of Information Systems, 83 Morska St., 81-225 Gdynia, Poland

Bibliografia

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• 2. Barbucha D.: Three approximation algorithms for solving the generalized segregated storage problem. European Journal of Operational Research, No. 156, 2004, p. 54-72.
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• 6. Jedrzejowicz P.: Social Learning Algorithm as a Tool for Solving Some Difficult Scheduling Problems. Foundation of Computing and Decision Sciences, No. 24 (2), 1999, p. 51-66.
• 7. Laporte G., Gendreau M., Potvin J., Semet F.: Classical and modem heuristics for the vehicle routing problem. International Transactions in Operational Research, No. 7, 2000, p. 285-300.
• 8. List G. F., Mirchandani P. B., Turnquist M. A., Zografos K. G.: Modeling and analysis for hazardous materials transportation: Risk analysis, routing/scheduling and facility location. Transportation Science, No. 25, 1991, p. 100-114.
• 9. Osman I. H.: Metastrategy Simulated Annealing and Tabu Search Algorithms for Vehicle Routing Problem. Annals of Operations Research, No. 41, 1993, p. 421-451
• 10. Thangiah S. R.: Vehicle Routing with Time Windows using Genetic Algorithms. [In:] Chambers, L. (ed.): Application Handbook of Genetic Algorithms: New Frontiers. Vol. II, CRC Press, Boca Raton, 1995, p. 253-277.
• 11. Toth P., Vigo D.: The Vehicle Routing Problem. SIAM Monographs Discrete Mathematics and Applications. Philadelphia, 2002.
• 12. Zografos K. G., Androutsopoulos K. N.: A heuristic algorithm for solving a hazardous materials distribution problems. European Journal of Operational Research, No. 152, 2004, p. 507-519.
• 13. Using a CPLEX Callable Library. CPLEX Optimization, Inc., 1995.