Abstract
This paper presents two greedy scheduling algorithms for recovery of damaged lifeline network. Unlike genetic algorithms or simulated annealing, the proposed algorithms do not involve random processes. One of the algorithm is for assigning multiple heterogeneous engineers and prepare schedules for repairing independent damaged components, while the other is for finding repair schedule for a single engineer considering network constraint. Both the algorithms uses rate of benefit gain as an index in deciding which component should be repaired next by whom. The target application of these algorithms is to serve as an initial solution for a multi agent system which includes fine grain details. With numerical experiments, it is demonstrated that the proposed algorithms can find near-optimal repair schedules and solve problems involving large number of variables.
