Abstract

Natural disasters, such as hurricanes, large wind and ice storms, typically require the repair of a large number of com- ponents in electricity distribution networks. Since power cannot be restored before the completion of repairs, optimally scheduling the available crews to minimize the cu- mulative duration of the customer interruptions reduces the harm done to the affected community. We have previously proposed approximation algorithms to schedule post-disaster repairs in electricity distribution networks with complete damage information[1]. In this paper, we extend our pre- vious work to the case with incomplete damage information. We model this problem as scheduling a set of jobs with stochastic processing times on parallel identical machines in order to minimize the total weighted energization time. A linear programming (LP) based list scheduling pol- icy is proposed and then analyzed in terms of theoretical performance.

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