Emergency material allocation with time-varying supply-demand based on dynamic optimization method for river chemical spills
- 13 Downloads
Aiming to minimize the damage caused by river chemical spills, efficient emergency material allocation is critical for an actual emergency rescue decision-making in a quick response. In this study, an emergency material allocation framework based on time-varying supply-demand constraint is developed to allocate emergency material, minimize the emergency response time, and satisfy the dynamic emergency material requirements in post-accident phases dealing with river chemical spills. In this study, the theoretically critical emergency response time is firstly obtained for the emergency material allocation system to select a series of appropriate emergency material warehouses as potential supportive centers. Then, an enumeration method is applied to identify the practically critical emergency response time, the optimum emergency material allocation and replenishment scheme. Finally, the developed framework is applied to a computational experiment based on south-to-north water transfer project in China. The results illustrate that the proposed methodology is a simple and flexible tool for appropriately allocating emergency material to satisfy time-dynamic demands during emergency decision-making. Therefore, the decision-makers can identify an appropriate emergency material allocation scheme in a balance between time-effective and cost-effective objectives under the different emergency pollution conditions.
KeywordsEnvironmental emergency management Emergency material allocation Time-varying supply-demand River chemical spills
The authors are extremely grateful to the editors and anonymous reviewers for their insightful comments and suggestions.
- Amini Salehi M, Smith J, Maciejewski AA, Siegel HJ, Chong EKP, Apodaca J, Briceño LD, Renner T, Shestak V, Ladd J, Sutton A, Janovy D, Govindasamy S, Alqudah A, Dewri R, Prakash P (2016) Stochastic-based robust dynamic resource allocation for independent tasks in a heterogeneous computing system. J Parallel Distrib Comput 97:96–111CrossRefGoogle Scholar