Effective algorithm for handling constraints in generator maintenance scheduling

Abstract

An effective algorithm for handling constraints to solve the generator maintenance scheduling (GMS) problem is presented. The proposed algorithm of constraint logic programming (CLP) synthesises logic programming, constraint satisfaction technique (CST), and branch and bound search schemes to provide an efficient and flexible approach to the problem. The constraints of the problem cannot only be conveniently managed by the logic programming but also be actively used to reduce the search space by the CST. Once the infeasible solutions are pruned away from the search space, the depth-first branch and bound search strategy is then used for determining the optimal solution. The practical GMS problem of Taiwan Power (Taipower) system is solved by the proposed CLP algorithm for demonstrating its effectiveness. To exhibit the efficiency of the proposed algorithm, the results obtained are compared with those from the established methods of simulated annealing (SA) and lagrangian relaxation (LR).