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A robust optimization approach for humanitarian needs assessment planning under travel time uncertainty

İsim	A robust optimization approach for humanitarian needs assessment planning under travel time uncertainty
Yazar	Koyuncu, Burcu Balçık, Yanıkoğlu, İhsan
Basım Tarihi:	2020-04-01
Basım Yeri	- Elsevier
Konu	Humanitarian logistics, Needs assessment, Robust optimization, Routing, Travel time uncertainty
Tür	Süreli Yayın
Dil	İngilizce
Dijital	Evet
Yazma	Hayır
Kütüphane:	Özyeğin Üniversitesi
Demirbaş Numarası	0377-2217
Kayıt Numarası	6997b336-bc0f-4f1a-9de0-407e67d30745
Lokasyon	Industrial Engineering
Tarih	2020-04-01
Notlar	TÜBİTAK
Örnek Metin	We focus on rapid needs assessment operations conducted immediately after a disaster to identify the urgent needs of the affected community groups, and address the problem of selecting the sites to be visited by the assessment teams during a fixed assessment period and constructing assessment routes under travel time uncertainty. Due to significant uncertainties in post-disaster transportation network conditions, only rough information on travel times may be available during rapid needs assessment planning. We represent uncertain travel times simply by specifying a range of values, and implement robust optimization methods to ensure that each constructed route is feasible for all realizations of the uncertain parameters that lie in a predetermined uncertainty set. We present a tractable robust optimization formulation with a coaxial box uncertainty set due to its advantages in handling uncertainty in our selective assessment routing problem, in which the dimension of the uncertainty (number of arcs traversed) is implicitly determined. To solve the proposed model efficiently, we develop a practical method for evaluating route feasibility with respect to the robust route duration constraints, and embed this feasibility check procedure in a tabu search heuristic. We present computational results to evaluate the effectiveness of our solution method, and illustrate our approach on a case study based on a real-world post-disaster network.
DOI	10.1016/j.ejor.2019.09.008
Cilt	282

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Özyeğin Üniversitesi

A robust optimization approach for humanitarian needs assessment planning under travel time uncertainty

Yazar Koyuncu, Burcu Balçık, Yanıkoğlu, İhsan

Basım Tarihi 2020-04-01

Basım Yeri - Elsevier

Konu Humanitarian logistics, Needs assessment, Robust optimization, Routing, Travel time uncertainty

Tür Süreli Yayın

Dil İngilizce

Dijital Evet

Yazma Hayır

Kütüphane Özyeğin Üniversitesi

Demirbaş Numarası 0377-2217

Kayıt Numarası 6997b336-bc0f-4f1a-9de0-407e67d30745

Lokasyon Industrial Engineering

Tarih 2020-04-01

Notlar TÜBİTAK

Örnek Metin We focus on rapid needs assessment operations conducted immediately after a disaster to identify the urgent needs of the affected community groups, and address the problem of selecting the sites to be visited by the assessment teams during a fixed assessment period and constructing assessment routes under travel time uncertainty. Due to significant uncertainties in post-disaster transportation network conditions, only rough information on travel times may be available during rapid needs assessment planning. We represent uncertain travel times simply by specifying a range of values, and implement robust optimization methods to ensure that each constructed route is feasible for all realizations of the uncertain parameters that lie in a predetermined uncertainty set. We present a tractable robust optimization formulation with a coaxial box uncertainty set due to its advantages in handling uncertainty in our selective assessment routing problem, in which the dimension of the uncertainty (number of arcs traversed) is implicitly determined. To solve the proposed model efficiently, we develop a practical method for evaluating route feasibility with respect to the robust route duration constraints, and embed this feasibility check procedure in a tabu search heuristic. We present computational results to evaluate the effectiveness of our solution method, and illustrate our approach on a case study based on a real-world post-disaster network.

DOI 10.1016/j.ejor.2019.09.008

Cilt 282