The backfill mining method is adopted in many mines around the world because it can reliably handle underground mine tailings and eliminate dangers in goafs. It is necessary to improve backfilling resource allocation and efficiency, thereby eliminating safety hazards and providing reliable support for the next stage of mining as quickly as possible. In this paper, we propose a backfill-scheduling optimization model that considers multiple processes, resource constraints, and operating capabilities. The purpose of this model is to minimize the exposure time of goafs. This NP-hard (Nondeterministic Polynomial-time hard) problem has a non-inferior implemented solution through multiple iterations of genetic, crossover, and mutation operations of the genetic algorithm. The results show that the model significantly reduces the backfilling-delay time and backfilling-operation time.
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