A robust counterpart approach to the bi-objective emergency medical service design problem

Zhang, Zhi‐Hai; Jiang, Hai

doi:10.1016/j.apm.2013.07.028

Cited by 86 publications

(40 citation statements)

References 18 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Bozorgi-Amiri et al (2013) developed a multi-objective robust stochastic programming model to capture the uncertainty in demand, supply and cost by using scenarios approach. It is undeniable that the stochastic approach is superior to the deterministic approach in handling the uncertainty by allowing parameters to be statistically dependent, but just as Zhang and Jiang (2013) remarked that the uncertainty is hard to quantify through probability distribution functions in the emergency response. Moreover, Mete and Zabinsky (2010) admitted that scenario-based approach limits the number of possible states when faced with the disaster preparedness and response.…”

Section: Relief Logistics Problem Under Uncertaintymentioning

confidence: 99%

“…As far as humanitarian relief logistics is concerned, only in recent years has the robust approach been applied in this field. Zhang and Jiang (2013) contemplated the uncertain parameters in the station location and emergency medical service assignment problem. They model a bi-objective robust counterpart formulation to find the Paretooptimal solutions for costs and response times.…”

Section: Relief Logistics Problem Under Uncertaintymentioning

confidence: 99%

See 1 more Smart Citation

A robust approach to the two-level humanitarian relief operation

Yaping

2017

IJEM

View full text Add to dashboard Cite

During the initial disaster response phase, an important issue in humanitarian relief logistics is to tackle the complexity of decision-making that covers the appropriate relief allocation and the associated transportation plan. We propose a two-level modelling methodology to alleviate that challenge, where the upper-level model focuses on the strategic relief distribution policy among the recipients whereas the lower-level model deals with the transportation routes, vehicle deployment and loading problems at the operational level based on the upper-level solution. Furthermore, in view of the demand uncertainty in impacted areas, a robust model is developed to guarantee the feasibility of relief distribution solutions. Also, a case study is conducted to illustrate the benefit of the presented robust framework, which is not only favourable in terms of the reliability and equity level relative to the deterministic one but also capable of offering advice on the vehicle arrangement.

show abstract

Section: Relief Logistics Problem Under Uncertaintymentioning

confidence: 99%

Section: Relief Logistics Problem Under Uncertaintymentioning

confidence: 99%

A robust approach to the two-level humanitarian relief operation

Yaping

2017

IJEM

View full text Add to dashboard Cite

show abstract

“…In EMS study, a stochastic programming approach has been proposed to design a robust EMS, which is to achieve a reliable level of service and minimize the operation cost [31]. A bi-objective model was developed to design a cost-responsiveness efficient emergency medical services (EMS) system under uncertainty [32], the approach determines the location of EMS stations, the assignment of demand areas to EMS stations, and the number of EMS vehicles at each station to balance cost and responsiveness by using a robust counterpart approach to deal with uncertain demand.…”

Section: Literature Reviewmentioning

confidence: 99%

Measuring Selection Diversity of Emergency Medical Service for Metro Stations: A Case Study in Beijing

Zhang

Jia

Qin

2018

IJGI

View full text Add to dashboard Cite

Abstract:It is important for station managers and emergency medical service (EMS) managers to understand the available ambulance stations for each metro station. EMS managers can make use of this information to reallocate EMS resources to improve the performance of EMS system. Station managers can pay attention to the safety management of metro stations with fewer medical rescue support. This paper aims to develop a selection diversity index to address two questions: "How many available ambulance stations are available or can serve the rescue of metro stations in emergency?" and "Which ambulance stations are most vulnerable?". To implement this measure in practice, definition of available ambulance stations for rescue of metro stations is described based on the response time threshold. The selection diversity is proposed to measure the preparability of medical rescue service for metro stations. To show proof of concept, a real-world case is presented to demonstrate the feasibility of the selection diversity index.

show abstract

“…Although there are some studies in the literature that propose multi-objective models for HRL problem (Lin et al, 2011;Bozorgi-Amiri et al, 2013;Najafi et al, 2013;Zhang and Jiang, 2013), multi-objective optimization that considers simultaneously time and cost as objectives in the specific category of LRDSP in HRL has never been addressed. This paper presents a novel bi-objective mixed-integer programming model for a HRL problem in the specific category of LRDSP.…”

Section: Introductionmentioning

confidence: 99%

Robust humanitarian relief logistics network planning

Rezaei-Malek¹,

Tavakkoli–Moghaddam

2014

10.5267/j.uscm

View full text Add to dashboard Cite

In recent years, death toll of natural and man-made disasters has increased at an appalling rate. Thus, disaster management and especially efficient management of humanitarian relief efforts seem to be essential. This paper presents a bi-objective mixed-integer mathematical model for Humanitarian Relief Logistics (HRL) operations planning, as an important part of the humanitarian relief efforts. This model determines optimal policies including location of warehouses, quantity of emergency relief items that should be held at each warehouse, and distribution plan to provide an emergency response pre-positioning strategy for disasters by considering two objectives. The first one minimizes the average response time and the second one minimizes the total operational cost including the fixed cost of establishing warehouses, the holding cost of unused supplies and the penalty cost of unsatisfied demand. The survival of prepositioned supplies, demand amount and routes condition following an event are considered under uncertainty in the model solved by a robust scenario-based approach. The robust approach is applied to reduce the effects of fluctuations of the uncertain parameters with regards to all the possible future scenarios. The research demonstrates the applicability and usefulness of the proposed model on a case study on earthquake preparation in the Seattle area in USA. In addition, the work applies the Reservation Level Tchebycheff Procedure (RLTP) method to solve the bi-objective model in an interactive way with decision maker. This work provides practitioners, specifically planning teams, with a new approach to assist with disaster preparedness and to improve their logistics decisions.

show abstract

A robust counterpart approach to the bi-objective emergency medical service design problem

Cited by 86 publications

References 18 publications

A robust approach to the two-level humanitarian relief operation

A robust approach to the two-level humanitarian relief operation

Measuring Selection Diversity of Emergency Medical Service for Metro Stations: A Case Study in Beijing

Robust humanitarian relief logistics network planning

Contact Info

Product

Resources

About