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Citation |
Chi H, Li J, Shao X, Gao M. Eur. J. Oper. Res. 2017; 258(3): 1022-1032. |
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Copyright |
(Copyright © 2017, Elsevier Publishing) |
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DOI |
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PMID |
unavailable |
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Abstract |
Most current research describes emergency resource scheduling as a multi-objective optimization problem. Each objective contributes to scheduling comprehensive effects. In many cases, goals are correlated. For example, reducing the scheduling time requires more resources and costs. Thus, an effect that approaches reality should be observed under conditions of mutual matching and combined roles of objectives. This study constructs a non-linear timeliness evaluation function for emergency resource scheduling that incorporates a single affected point, multiple supply centers and one type of resource, which combines two scheduling objectives, i.e., time and resource satisfaction, into a timeliness function. The evaluation function is a monotonically increasing function and a monotonically decreasing function with respect to the quantity and time of two batches of resource arrivals, respectively. Function values change within the range of demands for quantity and time of resources arrivals, but function values change little beyond the range of the demands, which is highly consistent with qualitative cognition. This study considers real mine water leak accidents and calculates the time for the water level in the mine to drop to the safety line using a simulation method according to the mechanism of water level change caused by the mine structure, water leakage flow and pumping, and then implements contrastive analyses of the results of the timeliness evaluation function and simulation method, and then concludes that timeliness evaluation functions are reasonable and require less information and less detail. This research provides new insight into the design of objective functions utilized in emergency resource scheduling. Language: en |
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Keywords |
Decision analysis; Emergency management; Emergency resources scheduling; Mines water leak; Timeliness evaluation |