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020 ▼a 9781088350591
035 ▼a (MiAaPQ)AAI13904889
040 ▼a MiAaPQ ▼c MiAaPQ ▼d 247004
0820 ▼a 658
1001 ▼a Azghandi, Rana.
24510 ▼a Analytic Models for Effective Planning for Response to Sudden Disruptions.
260 ▼a [S.l.]: ▼b Northeastern University., ▼c 2019.
260 1 ▼a Ann Arbor: ▼b ProQuest Dissertations & Theses, ▼c 2019.
300 ▼a 111 p.
500 ▼a Source: Dissertations Abstracts International, Volume: 81-05, Section: B.
500 ▼a Advisor: Griffin, Jacqueline.
5021 ▼a Thesis (Ph.D.)--Northeastern University, 2019.
506 ▼a This item must not be sold to any third party vendors.
506 ▼a This item must not be added to any third party search indexes.
520 ▼a All systems, and particularly complex systems are vulnerable to disruptive events including large disruptions, which are easily detected and quickly responded to, and small disruptions, which are more difficult to detect. Due to the differences in the ability to detect and forecast the effects of small disruptions, more focus is often given to preparations for major disruptions. However, neglecting minor disruptive events may lead to more severe problems in the long run. Due to the need to focus on how to plan to respond to disruptions of multiple scales, this dissertation focuses on critical problems in two application areas: (i) addressing the needs of elderly and disabled populations in natural disasters, and (ii) addressing the underlying causes of pharmaceutical drug shortages nationwide.
590 ▼a School code: 0160.
650 4 ▼a Industrial engineering.
690 ▼a 0546
71020 ▼a Northeastern University. ▼b Mechanical and Industrial Engineering.
7730 ▼t Dissertations Abstracts International ▼g 81-05B.
773 ▼t Dissertation Abstract International
790 ▼a 0160
791 ▼a Ph.D.
792 ▼a 2019
793 ▼a English
85640 ▼u http://www.riss.kr/pdu/ddodLink.do?id=T15492571 ▼n KERIS ▼z 이 자료의 원문은 한국교육학술정보원에서 제공합니다.
980 ▼a 202002 ▼f 2020
990 ▼a ***1008102
991 ▼a E-BOOK