Personnel scheduling and supplies provisioning in emergency relief operations

Annals of Operations Research

Volumn 235, Issue 1, 2015, Pages 487-515

  Lei, Lei ^a   Pinedo, Michael ^b   Qi, Lian ^a   Wang, Shengbin ^c   Yang, Jian ^a  

^a RUTGERS UNIVERSITY   (United States)

^b NEW YORK UNIVERSITY   (United States)

^c NORTH CAROLINA A AND T STATE UNIVERSITY   (United States)

Author keywords

Emergency operations scheduling; Empirical results; Mathematical programming based heuristics; Renewable and non renewable resource constraints; Tardiness minimization

Indexed keywords

EID: 84948579482     PISSN: 02545330     EISSN: 15729338     Source Type: Journal    
DOI: 10.1007/s10479-015-1990-6     Document Type: Article

References (55)

1. Afshar, A., & Haghani, A. (2012). Modeling integrated supply chain logistics in real-time large-scale disaster relief operations. Socio-Economic Planning Sciences, 46(4), 327–338.
2. Ahuja, R., Magnanti, T., & Orlin, J. (1993). Network flows: Theory, algorithms, and applications. Upper Saddle River: Prentice Hall.
3. Ait-Kadia, D., Menye, J. B., & Kane, H. (2011). Resources assignment model in maintenance activities scheduling. International Journal of Production Research, 49(22), 6677–6689.
4. Assaf, S. A., & Al-Hejji, S. (2006). Causes of delay in large construction projects. International Journal of Project Management, 24(4), 349–357.
5. Bachlaus, M., Tiwari, M. K., & Chan, F. T. S. (2009). Multi-objective resource assignment problem in a product-driven supply chain using a Taguchi-based DNA algorithm. International Journal of Production Research, 47(9), 2345–2371.
6. Balcik, B., Beamon, B., Krejci, C., Muramatsu, K., & Ramirez, M. (2010). Coordination in humanitarian relief chains: Practices, challenges and opportunities. International Journal of Production Economics, 126(1), 22–34.
7. Barbarosoglu, G., & Arda, Y. (2004). A two-stage stochastic programming framework for transportation planning in disaster response. Journal of the Operational Research Society, 55(1), 43–53.
8. Barbarosoglu, G., Ozdamar, L., & Cevik, A. (2002). An interactive approach for hierarchical analysis of helicopter logistics in disaster relief operations. European Journal of Operational Research, 140, 118–133.
9. Becker’s Hospital Review. (2011). 50 largest hospitals in America. http://www.beckershospitalreview.com/lists/50-largest-hospitals-in-america.html. Retrieved April 24, 2015.
10. Beraldi, P., Ghiani, G., Grieco, A., & Guerriero, E. (2008). Rolling-horizon and fix-and-relax heuristics for the parallel machine lot-sizing and scheduling problem with sequence-dependent set-up costs. Computers & Operations Research, 35(11), 3644–3656.
11. Bottcher, J., Drexl, A., Kolisch, R., & Salewski, F. (1999). Project scheduling under partially renewable resource constraints. Management Science, 45(4), 543–559.
12. Brenner, U. (2008). A faster polynomial algorithm for the unbalanced Hitchcock transportation problem. Operations Research Letters, 36(4), 408–413.
13. Brucker, P., & Kramer, A. (1996). Polynomial algorithms for resource-constrained and multiprocessor task scheduling problems. European Journal of Operational Research, 90(2), 214–226.
14. Caunhye, A., Nie, X., & Pokharel, S. (2012). Optimization models in emergency logistics: A literature review. Socio-Economic Planning Sciences, 46(1), 4–13.
15. Celano, G., Costa, A., & Fichera, S. (2008). Scheduling of unrelated parallel manufacturing cells with limited human resources. International Journal of Production Research, 46(2), 405–427.
16. Chan, F., Wong, T., & Chan, L. (2006). Flexible job-shop scheduling problem under resource constraints. International Journal of Production Research, 44(11), 2071–2089.
17. Cooke, J. (2012). Asian disasters drive firms to boost safety stock. DC Velocity, April 16, 2012. http://www.dcvelocity.com/articles/20120416-asian-disasters-drive-firms-to-boost-safety-stock/. Retrieved April 24, 2015.
18. de Araujo, S., Arenales, M., & Clark, A. (2007). Joint rolling-horizon scheduling of materials processing and lot-sizing with sequence-dependent setups. Journal of Heuristics, 13(4), 337–358.
19. Debels, D., & Vanhoucke, M. (2007). A decomposition-based genetic algorithm for the resource-constrained project-scheduling problem. Operations Research, 55(3), 457–469.
20. Deblaere, F., Demeulemeester, E., Herroelen, W., & Van de Vonder, S. (2007). Robust resource allocation decisions in resource-constrained projects. Decision Sciences, 38(1), 5–37.
21. Depuy, G., & Whitehouse, G. (2001). A simple and effective heuristic for the resource constrained project-scheduling problem. International Journal of Production Research, 39(14), 3275–3287.
22. Eckstein, A., & Rohleder, T. (1998). Incorporating human resources in group technology cellular manufacturing. International Journal of Production Research, 36(5), 1199–1222.
23. Federal Emergency Management Agency (FEMA). (2006). Disaster medical assistance teams provide crucial support in New Orleans, February 28, 2006. https://www.fema.gov/news-release/2006/02/28/disaster-medical-assistance-teams-provide-crucial-support-new-orleans. Retrieved April 24, 2015.
24. Frid, M. J. (2011). Extreme flooding along the coast due to earthquake and tsunami, March 12, 2011. http://martinjapan.blogspot.com/2011/03/extreme-flooding-along-coast-due-to.html. Retrieved April 24, 2015.
25. Gagnon, M., D’Avignona, G., & Boctor, F. (2009). An algorithm for the MRCPS problem with renewal and non-renewal resource types. Quebec: Faculty of Business Administration, Laval University.
26. Geismar, N., Laporte, G., Lei, L., & Sriskandarajah, C. (2008). The integrated production and transportation scheduling problem with a short lifespan product and non-instantaneous transportation time. INFORMS Journal on Computing, 20(1), 21–33.
27. Haghani, A., & Oh, S. (1996). Formulation and solution of a multi-commodity, multi-modal network flow model for disaster relief operations. Transportation Research Part A: Policy and Practice, 30(3), 231–250.
28. Hartmann, S., & Briskorn, D. (2010). A survey of variants and extensions of the resource-constrained project scheduling problem. European Journal of Operational Research, 207(1), 1–14.
29. Huang, M., Smilowitz, K., & Balcik, B. (2012). Models for relief routing: Equity, efficiency and efficacy. Transportation Research Part E, 48(1), 2–18.
30. Hwang, N. C., & Kogan, K. (2003). Dynamic approach to human resources planning for major professional companies with a peak-wise demand. International Journal of Production Research, 41(6), 1255–1271.
31. International Federation of Red Cross and Red Crescent Societies. (2011). Annual report on international disaster response laws, rules and principles (IDRL) programme, April 23, 2012. http://www.ifrc.org/docs/Appeals/11/MAA0000411ar.pdf. Retrieved April 24, 2015.
32. Karsu, O., & Azizoglu, M. (2012). The multi-resource agent bottleneck generalized assignment problem. International Journal of Production Research, 50(2), 309–324.
33. Klein, R. (2000). Project scheduling with time-varying resource constraints. International Journal of Production Research, 38(16), 3937–3952.
34. Kros, J. E., & Brown, E. (2013). Health care operations and supply chain management: Strategy, operations, planning, and control (1st ed.). Hoboken: Jossey-Bass.
35. Lee, C. Y., & Lei, L. (2001). Multiple-project scheduling with controllable project duration and hard resource constraint: Some solvable cases. Annals of Operations Research, 102(1–4), 287–307.
36. Lee, K., Lei, L., Pinedo, M., & Wang, S. (2013). Operations scheduling with multiple resources and transportation considerations. International Journal of Production Research, 51(23–24), 7071–7090.
37. Lei, L., Zhong, H., & Chaovalitwongse, W. (2009). On the integrated production and distribution problem with bidirectional flows. INFORMS Journal on Computing, 21(4), 585–598.
38. Li, Z., & Ierapetritou, M. (2010). Rolling horizon based planning and scheduling integration with production capacity consideration. Chemical Engineering Science, 65(22), 5887–5900.
39. Nolz, P., Semet, F., & Doerner, K. (2011). Risk approaches for delivering disaster relief supplies. OR Spectrum, 33(3), 543–569.
40. Nudtasomboon, N., & Randhawa, S. (1997). Resource-constrained project scheduling with renewable and non-renewable resources and time-resource tradeoffs. Computers & Industrial Engineering, 32(1), 227–242.
41. Özdamar, L., Ekinci, E., and Küçükyazici, B. (2004). Emergency logistics planning in natural disasters. Annals of Operations Research, 129, 217–245.
42. Qi, L. (2013). A continuous-review inventory model with random disruptions at the primary supplier. European Journal of Operational Research, 225(1), 59–74.
43. Salmeron, J., & Apte, A. (2010). Stochastic optimization for natural disaster asset prepositioning. Production and Operations Management, 19(5), 561–574.
44. Sonia, & Puri, M. (2004). Two level hierarchical time minimizing transportation problem. Top, 12(2), 301–330.
45. Times-News. (2013). The Alamance Scene: Blood needed in Oklahoma tornado aftermath, May 24, 2013. http://www.thetimesnews.com/news/top-news/the-alamance-scene-blood-needed-in-oklahoma-tornado-aftermath-1.148471. Retrieved April 24, 2015.
46. Tomlin, B. T. (2006). On the value of mitigation and contingency strategies for managing supply-chain disruption risks. Management Science, 52(5), 639–657.
47. USNews Health. (2014). Best hospitals in New York, NY. http://health.usnews.com/best-hospitals/area/new-york-ny (2014-2015 version). Retrieved April 24, 2015.
48. Van de Vonder, S., Demeulemeester, E., Herroelen, W., & Leus, R. (2006). The trade-off between stability and makespan in resource-constrained project scheduling. International Journal of Production Research, 44(2), 215–236.
49. Van Peteghem, V., & Vanhoucke, M. (2014). An experimental investigation of metaheuristics for the multi-mode resource-constrained project scheduling problem on new dataset instances. European Journal of Operational Research, 235, 62–72.
50. Vanhoucke, M., Demeulemeester, E., & Herroelen, W. (2001). An exact procedure for the resource-constrained weighted earliness-tardiness project scheduling problem. Annals of Operations Research, 102(1–4), 179–196.
51. Walton, R., Mays, R., Haselkorn, M. (2011). Defining “fast”: Factors affecting the experience of speed in humanitarian logistics. In Proceedings of the 8th international ISCRAM conference, Lisbon, Portugal, May 2011, pp. 1–10. https://www.purdue.edu/discoverypark/vaccine/assets/pdfs/publications/pdf/Factors%20Affecting%20the%20Experience%20of%20Speed%20in%20Humanitarian%20Logistics.pdf. Retrieved April 24, 2015.
52. Weglarz, J., Jozefowska, J., Mika, M., & Waligora, G. (2011). Project scheduling with finite or infinite number of activity processing modes—A survey. European Journal of Operational Research, 208, 177–205.
53. Wong, C., Chan, F., & Chung, S. (2013). A joint production scheduling approach considering multiple resources and preventive maintenance tasks. International Journal of Production Research, 51(3), 883–896.
54. Yi, W., & Kumar, A. (2007). Ant colony optimization for disaster relief operations. Transportation Research Part E: Logistics and Transportation Review, 43(6), 660–672.
55. Yi, W., & Ozdamar, L. (2007). A dynamic logistics coordination model for evacuation and support in disaster response activities. European Journal of Operational Research, 179, 1177–1193.