This paper considers a humanitarian logistics network(HTLN)design problem,including the emergency relief facilities(ERFs)location-allocation decision for the efficient distribution of emergency supplies from the ERFs ...This paper considers a humanitarian logistics network(HTLN)design problem,including the emergency relief facilities(ERFs)location-allocation decision for the efficient distribution of emergency supplies from the ERFs to the affected areas.A goal programming(GP)approach is applied to consider the multiple objectives simultaneously.Solving the GP model with a given weight assigned to each goal yields a single HTLN scheme,so there will be various schemes available by solving the GP with multiple values of the weights.For evaluating these schemes and identifying the most efficient one,we apply the data envelopment analysis(DEA)methods considering each scheme as a decision-making unit(DMU).Since the classical DEA(C-DEA)intrinsically aims to identify efficient DMUs and the efficient frontier,the use of C-DEA may not lead to a full ranking in many situations.There are several independent evaluation approaches to increasing discriminating power.Among them,this study integrates the multiple criteria DEA(MC-DEA)with the following three DEA methods,(i)stratification DEA(S^DEA),(ii)cross-efficiency DEA(CE-DEA),and(iii)super-efficiency DEA(SE-DEA),to make the most use of each method's strengths.Through a case study of designing the HTLN system for South Carolina,the procedure of implementing the integrated multiple criteria DEA(IMC-DEA)method is demonstrated.It is observed that the IMCDEA method performs well in terms of designing the HTLN system and would help the decision-makers consider more efficient options and make a final decision.展开更多
Particularly in the early phases of a disaster,logistical decisions are needed to be made quickly and under high pressure for the decision-makers,knowing that their decisions may have direct consequences on the affect...Particularly in the early phases of a disaster,logistical decisions are needed to be made quickly and under high pressure for the decision-makers,knowing that their decisions may have direct consequences on the affected society and all future decisions.Proactive risk reduction may be helpful in providing decision-makers with optimal strategies in advance.However,disasters are characterized by severe uncertainty and complexity,limited knowledge about the causes of the disaster,and continuous change of the situation in unpredicted ways.Following these assumptions,we believe that adequate proactive risk reduction measures are not practical.We propose strengthening the focus on ad hoc decision support to capture information in almost real time and to process information efficiently to reveal uncertainties that had not been previously predicted.Therefore,we present an ad hoc decision support system that uses scenario techniques to capture uncertainty by future developments of a situation and an optimization model to compute promising decision options.By combining these aspects in a dynamic manner and integrating new information continuously,it can be ensured that a decision is always based on the best currently available and processed information.And finally,to identify a robust decision option that is provided as a decision recommendation to the decision-makers,methods of multi-attribute decision making(MADM)are applied.Our approach is illustrated for a facility location decision problem arising in humanitarian relief logistics where the objective is to identify robust locations for tent hospitals to serve injured people in the immediate aftermath of the Haiti Earthquake 2010.展开更多
Post-event response planners must develop effective and efficient plans for the proper allocation and distribution of resources to impacted areas （IAs） within a critical time window. To determine the effectiveness a...Post-event response planners must develop effective and efficient plans for the proper allocation and distribution of resources to impacted areas （IAs） within a critical time window. To determine the effectiveness and efficiency of distribution plans, this study addresses resource allocation effectiveness losses （RAEL, or losses caused by the mismatch between supply and demand in IAs） and emergency logistics time costs （ELTC, or transportation time of logistics processes under emergency conditions）. Moreover, this study examines a follow-up sharing character （FSC） that coordinates resources among different phases. This research proposes an integrated model （IM） based on this character. This model aims to minimize RAEL and ELTC. Furthermore, the IM combines the time dimension model （TDM）, which coordinates the demands and supplies of all phases in the planning horizon, and the space dimension model （SDM）, which generates a specific distribution plan for the first phase. An analytical solution is obtained for the TDM as per the definition of FSC, after which the SDM is solved through a single-objective linear programming model. After solving the IM effectively, we fred that the proposed methodology fits the emergency circumstance well. Insights derived from the model are also presented in the conclusion.）展开更多
基金the National Institute of Food and Agriculture,US Department of Agriculture,Evans-Alien project number SCX-313-04-18.
文摘This paper considers a humanitarian logistics network(HTLN)design problem,including the emergency relief facilities(ERFs)location-allocation decision for the efficient distribution of emergency supplies from the ERFs to the affected areas.A goal programming(GP)approach is applied to consider the multiple objectives simultaneously.Solving the GP model with a given weight assigned to each goal yields a single HTLN scheme,so there will be various schemes available by solving the GP with multiple values of the weights.For evaluating these schemes and identifying the most efficient one,we apply the data envelopment analysis(DEA)methods considering each scheme as a decision-making unit(DMU).Since the classical DEA(C-DEA)intrinsically aims to identify efficient DMUs and the efficient frontier,the use of C-DEA may not lead to a full ranking in many situations.There are several independent evaluation approaches to increasing discriminating power.Among them,this study integrates the multiple criteria DEA(MC-DEA)with the following three DEA methods,(i)stratification DEA(S^DEA),(ii)cross-efficiency DEA(CE-DEA),and(iii)super-efficiency DEA(SE-DEA),to make the most use of each method's strengths.Through a case study of designing the HTLN system for South Carolina,the procedure of implementing the integrated multiple criteria DEA(IMC-DEA)method is demonstrated.It is observed that the IMCDEA method performs well in terms of designing the HTLN system and would help the decision-makers consider more efficient options and make a final decision.
基金We would like to thank the German Federal Ministry ofEducation and Research (BMBF) for financial supportfor this work within the project SEAK.
文摘Particularly in the early phases of a disaster,logistical decisions are needed to be made quickly and under high pressure for the decision-makers,knowing that their decisions may have direct consequences on the affected society and all future decisions.Proactive risk reduction may be helpful in providing decision-makers with optimal strategies in advance.However,disasters are characterized by severe uncertainty and complexity,limited knowledge about the causes of the disaster,and continuous change of the situation in unpredicted ways.Following these assumptions,we believe that adequate proactive risk reduction measures are not practical.We propose strengthening the focus on ad hoc decision support to capture information in almost real time and to process information efficiently to reveal uncertainties that had not been previously predicted.Therefore,we present an ad hoc decision support system that uses scenario techniques to capture uncertainty by future developments of a situation and an optimization model to compute promising decision options.By combining these aspects in a dynamic manner and integrating new information continuously,it can be ensured that a decision is always based on the best currently available and processed information.And finally,to identify a robust decision option that is provided as a decision recommendation to the decision-makers,methods of multi-attribute decision making(MADM)are applied.Our approach is illustrated for a facility location decision problem arising in humanitarian relief logistics where the objective is to identify robust locations for tent hospitals to serve injured people in the immediate aftermath of the Haiti Earthquake 2010.
基金Acknowledgments This work is supported by the National Natural Science Foundation of China （Grant Nos. 71471162 and 71302033）, Humanities and Social Sciences Foundation of Ministry of Education of China （Grant No. 15YJCZH211） and Zhejiang Provincial Natural Science Foundation of China （Grant No. LQ 16G010005） The authors are extremely grateful to the editor and the anonymous reviewers for their insightful comments and valuable suggestions.
文摘Post-event response planners must develop effective and efficient plans for the proper allocation and distribution of resources to impacted areas （IAs） within a critical time window. To determine the effectiveness and efficiency of distribution plans, this study addresses resource allocation effectiveness losses （RAEL, or losses caused by the mismatch between supply and demand in IAs） and emergency logistics time costs （ELTC, or transportation time of logistics processes under emergency conditions）. Moreover, this study examines a follow-up sharing character （FSC） that coordinates resources among different phases. This research proposes an integrated model （IM） based on this character. This model aims to minimize RAEL and ELTC. Furthermore, the IM combines the time dimension model （TDM）, which coordinates the demands and supplies of all phases in the planning horizon, and the space dimension model （SDM）, which generates a specific distribution plan for the first phase. An analytical solution is obtained for the TDM as per the definition of FSC, after which the SDM is solved through a single-objective linear programming model. After solving the IM effectively, we fred that the proposed methodology fits the emergency circumstance well. Insights derived from the model are also presented in the conclusion.）
