Purpose -Emergency relief supply chain (ERSC) design is an important strategic decision that significantly affects the overall performance of emergency management activities. The performance of an ERSC can be measured by several performance measures some of which may conflict with each other. The purpose of this paper is to propose an ERSC design framework by simultaneously taking total logistics cost (TLC), risk level, and amount of demands covered in an ERSC into consideration. Design/methodology/approach -The study considers TLC of an ERSC as the sum of logistics cost from distribution warehouses (DWHs) to Break of Bulbs (BOBs) and from BOBs to affected neighborhoods. The risk level of an ERSC is measured by estimating the expected number of disrupted relief items (EDI) distributed from DWHs through BOBs to neighborhoods. The covered demand (CDM) is defined as total populations that are supported in case of an emergency, the populations within the maximal coverage distance (MCD) from relief facilities. Based on these performance measures, the authors formulate a Goal Programming (GP) model to distribute emergency relief items to affected locations. Ideal values of these performance measures are decided, and the GP model seeks to minimize the weighted sum of the percentage deviations of those performance measures from the ideal values. The relationships among performance measures have been thoroughly analyzed through detailed trade-off studies under two realistic case studies by changing weights of each performance measure. Findings -Three performance measures are interdependent over specific values of weights. TLC and EDI have a trade-off relationship when the weight on each measure increases. TLC and CDM also have a trade-off relationship when the weight on EDI increases. However, this relationship becomes less apparent when the MCD increases. EDI and CDM also have the same trade-off relationship when the weight on TLC changes. Therefore, decision makers should thoroughly analyze these trade-off relationships when they design ERSCs. Overall, the study identified that an ERSC with higher MCD outperforms one with lower MCD in terms of TLC, EDI, and CDM. Originality/value -The study presents a design framework to generate more balanced ERSCs by simultaneously taking three conflicting performance measures into consideration, and demonstrated the feasibility of the framework through realistic case studies. The trade-off analysis provides useful insights and theoretical knowledge to researchers and practitioners in the discipline of emergency logistics management. The results from this study are expected to contribute to the development of more balanced ERSCs.

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Abstract:Purpose: The purpose of this paper is to propose a simulation-based robust biofuel facility location model for solving an integrated bio-energy logistics network (IBLN) problem, where biomass yield is often uncertain or difficult to determine.Design/methodology/approach: The IBLN considered in this paper consists of four different facilities: farm or harvest site (HS), collection facility (CF), biorefinery (BR), and blending station (BS). Authors propose a mixed integer quadratic modeling approach to simultaneously determine the optimal CF and BR locations and corresponding biomass and bio-energy transportation plans. The authors randomly generate biomass yield of each HS and find the optimal locations of CFs and BRs for each generated biomass yield, and select the robust locations of CFs and BRs to show the effects of biomass yield uncertainty on the optimality of CF and BR locations. Case studies using data from the State of South Carolina in the United State are conducted to demonstrate the developed model's capability to better handle the impact of uncertainty of biomass yield. Findings:The results illustrate that the robust location model for BRs and CFs works very well in terms of the total logistics costs. The proposed model would help decision-makers find the most robust locations for biorefineries and collection facilities, which usually require huge -1415-Journal of Industrial Engineering and Management -http://dx.doi.org/10.3926/jiem.1196 investments, and would assist potential investors in identifying the least cost or important facilities to invest in the biomass and bio-energy industry.Originality/value: An optimal biofuel facility location model is formulated for the case of deterministic biomass yield. To improve the robustness of the model for cases with probabilistic biomass yield, the model is evaluated by a simulation approach using case studies.The proposed model and robustness concept would be a very useful tool that helps potential biofuel investors minimize their investment risk.

Four species of the genus Luzonomyza Malloch, 1929 from southwest China are described as new to science: Luzonomyza vittifacies Li & Yang, sp. nov., L. serrata Li & Yang, sp. nov., L. honghensis Li & Yang, sp. nov., and L. brevis Li & Yang, sp. nov. A key to Luzonomyza species is also presented.