Advertisement

Obnoxious Facility Location

  • Sara Hosseini
  • Ameneh Moharerhaye Esfahani
Chapter
Part of the Contributions to Management Science book series (MANAGEMENT SC.)

Abstract

In general, facilities are divided in two groups, the first one are desirable to the nearby inhabitants which try to have them as close as possible such as hospitals, fire stations, shopping stores and educational centers. The second group turns out to be undesirable for the surrounding population, which avoids them and tries to stay away from them such as garbage dump sites, chemical plants, nuclear reactors, military installations, prisons and polluting plants. In this sense, Daskin (1995) discussed that Erkut and Neuman in 1989 distinguished between Noxious (hazardous to health) and Obnoxious (nuisance to lifestyle) facilities, although both can be simply regarded as Undesirable. Moreover, in the last decade, a new nomenclature has been developed to define these oppositions: NIMBY (not in my back yard), NIMNBY (not in my neighbor’s back yard), and NIABY (not in anyone’s back yard).

Keywords

Hazardous Waste Goal Programming Model Vehicle Rout Problem With Time Window Accident Probability Demand Center 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. Akgun V, Erkut E, Batta R (2000) On finding dissimilar paths. Eur J Oper Res 121:232–246CrossRefGoogle Scholar
  2. Akgun V, Parekh A, Batta R, Rump C (2007) Routing of a hazmat tuck in the presence of weather systems. Comput Oper Res 34:1351–1373CrossRefGoogle Scholar
  3. Alumur S, Kara B (2007) A new model for the hazardous waste location-routing problem. Comput Oper Res 34:1406–1423CrossRefGoogle Scholar
  4. Batta R, Chiu SS (1988) Optimal obnoxious path on a network: Transportation of hazardous materials. Oper Res 36(1):84–92CrossRefGoogle Scholar
  5. Bell MGH (2006) Mixed strategies for the risk-averse shipment of hazardous materials. Spat Econ 6:253–265CrossRefGoogle Scholar
  6. Berman O, Verter V, Kara B (2007) Designing emergency response networks for hazardous materials transportation. Comput Oper Res 34:1374–1388CrossRefGoogle Scholar
  7. Cappanera P, Gallo G, Maffioli F (2004) Discrete facility location and routing of obnoxious activities. Discrete Appl Math 133:3–28CrossRefGoogle Scholar
  8. Carotenuto P, Giordani S, Ricciardelli S, Rismondo S (2007) A tabu search approach for scheduling hazmat shipments. Comput Oper Res 34:1328–1350CrossRefGoogle Scholar
  9. Castillo JE (2004) Route optimization for hazardous materials transport. International Institute for geo-Information science and earth observation, Enschede, The NetherlandsGoogle Scholar
  10. Ceceres T, A.Mesa J, Ortega F (2007) Locating waste pipelines to minimize their impact on marine environment. Eur J Oper Res 179(3):1143–1159Google Scholar
  11. Colebrook M, Guti J, Sicilia J (2005) A new bound and an O (mn) algorithm for the undesirable 1-median problem (Maxian) on networks. Comput Oper Res 32:309–325CrossRefGoogle Scholar
  12. Dadkar Y, Jones D, Nozick L (2008) Identifying geographically diverse routes for the transportation of hazardous materials. Transportation Research Part E: Logistics and Transportation Review 44(3):333–349Google Scholar
  13. Daskin MS (1995) Network and discrete location: models, algorithms and applications. Wiley, New YorkCrossRefGoogle Scholar
  14. Díaz-Báňez JM, Gómez F, Toussaint GT (2005) Computing shortest paths for transportation of hazardous materials in continuous spaces. J Food Eng 70:293–298CrossRefGoogle Scholar
  15. Drezner Z, Wesolowsky GO (1983) Location of an obnoxious facility with rectangular distances. J Reg Sci 23:241–248CrossRefGoogle Scholar
  16. Erkut E, Verter V (1995) Hazardous Materials Logistics. Springer Series in Oper Res, Chapter 20Google Scholar
  17. Erkut E, Verter V (1998) Modeling of transport risk for hazardous material. Oper Res 46(5): 625–642CrossRefGoogle Scholar
  18. Erkut E, Alp O (2007) Designing a network for hazardous materials shipments. Comput Oper Res 34(5):1389–1405CrossRefGoogle Scholar
  19. Erkut E, Gzara F (2008) Solving the hazmat transport network design problem. Comput Oper Res 35(7):2234–2247CrossRefGoogle Scholar
  20. Erkut E, Ingolfsson A (2005) Transport risk models for hazardous materials: revisited. Oper Res Lett 33:81–89CrossRefGoogle Scholar
  21. Fernandez J, Fernandez P, Pelegrin B (2000) A continuous location model for siting a non-noxious undesirable facility within a geographical region. Eur J Oper Res 121:259–274CrossRefGoogle Scholar
  22. Giannikos I (1998) A multi-objective programming model for locating treatment sites and routing hazardous wastes. Eur J Oper Res 104:333–342CrossRefGoogle Scholar
  23. Gopalan R, Kolluri KS, Batta R, Karwan MH (1990) Modeling equity of risk in the transportation of hazardous materials. Oper Res 38(6):961–973CrossRefGoogle Scholar
  24. Kara BY, Erkut E, Verter V (2003) Accurate calculation of hazardous materials transport risks. Oper Res Lett 31:285–292CrossRefGoogle Scholar
  25. Katz MJ, Kedem K, Segal M (2002) Improved algorithms for placing undesirable facilities. Comput Oper Res 29:1859–1872CrossRefGoogle Scholar
  26. Kuby MJ (1987) Programming models for facility dispersion: the p-dispersion and maxisum dispersion problems. Geographical Analysis 19:315–329Google Scholar
  27. Marianov V, ReVelle C (1998) Linear, no-approximated models for optimal routing in hazardous environments. J Operl Res Society 48:157–164Google Scholar
  28. McGinnis LF, White JA (1978) A single facility rectilinear location problem with multiple criteria. Transport Sci 12:217–231CrossRefGoogle Scholar
  29. Mehrez A, Sinuany-Stern Z, Stulman A (1986) An enhancement of the Drezner–Wesolowsky algorithm for single facility location with maximin of rectilinear distance. J Oper Res Soc 37:971–977Google Scholar
  30. Melachrinoudi E (1999) Bicriteria location of a semi-obnoxious facility. Comput Oper Res 37: 581–593Google Scholar
  31. Pisinger D (2006) Upper bounds and exact algorithms for p-dispersion problems. Comput Oper Res 33:1380–1398CrossRefGoogle Scholar
  32. Rakas J, Teodorovic D, Kim T (2004) Multi-objective modeling for determining location of undesirable facilities. Transport Re D9:125–138Google Scholar
  33. Revelle C, Cohon J, Shobrys D (1991) Simultaneous siting and routing in the disposal of hazardous wastes. Transportation Science 25(2):138–145Google Scholar
  34. Ratick S, White A (1988) A risk sharing model for locating noxious facilities. Environment Plan 165–179Google Scholar
  35. Rogers GO (1998) Sitting potentially hazardous facilities: What factors impact perceived and acceptable risk? Landsc Urban Plan 39:265–281CrossRefGoogle Scholar
  36. Rodriguez JJ, Garcia GC, Muñoz Pérez J Mérida Casermeiroa E (2006) A general model for the undesirable single facility location problem. Oper Res Lett 34(4):427–436CrossRefGoogle Scholar
  37. Saccomanno FF, Chan A (1985) Economic evaluation of routing strategies for hazardous road shipments. Transp. Res. Record 1020:12–18Google Scholar
  38. Sivakumar R, Batta R, Karwan MH (1993) A network- based model for transporting extremely hazardous materials. Oper Res Lett 13(2):85–93CrossRefGoogle Scholar
  39. Sivakumar R, Batta R, Karwan MH (1995) A multiple route conditional risk model for transporting hazardous materials. INFOR 33:20–33Google Scholar
  40. Wayman MM, Kuby M (1994) Proactive optimization: General framework and a case study using a toxic waste location model with technology choice. International symposium on locational decisions, ISOLDE VI, Lesvos and Chios, GreeceGoogle Scholar
  41. Yapicioglu H, Smith AE, Dozier G (2007) Solving the semi- obnoxious facility location problem using bi-objective particle swarm. Eur J Oper Res 177:733–749CrossRefGoogle Scholar
  42. Zhang J, Hodgson J, Erkut E (2000) Using GIS to assess the risk of hazardous materials transport in networks. Eur J Oper Res 121:316–329CrossRefGoogle Scholar
  43. Zhang L, Guo S, Zhu Y, Lim A (2005) A tabu search algorithm for the safe transportation of hazardous materials. Proceedings of the ACM symposium on Applied computing, SESSION: Evolutionary computation and optimization (ECO), pp 940–946Google Scholar
  44. Zografos KG, Androutsopoulos KN (2004) A heuristic algorithm for solving hazardous materials distribution problems. Eur J Oper Res 152:507–519CrossRefGoogle Scholar
  45. Zografos KG, Vasilakis GM, Giannouli IM (2000) Methodological framework for developing decision support system (DSS) for hazardous materials emergency response operations. J Hazardous Mater 71:503–521CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  1. 1.Department of Industrial EngineeringAmirkabir University of TechnologyTehranIran

Personalised recommendations