지속가능한 전력망 점검 스케줄링을 위한 수리계획-발견적 복합 알고리즘 (A Hybrid Mathematical Programming-Heuristic Algorithm for a Sustainable Power Grid Maintenance Scheduling)

서지정보

· 발행기관 : 대한산업공학회
· 수록지 정보 : 대한산업공학회지 / 48권 / 1호 / 13 ~ 34페이지
· 저자명 : 주재관, 노영주, 박현우, 이제리미, 이충목

초록

This paper considers a stochastic job allocation problem inspired by a real-life electric power grid operator. The power grid requires regular maintenance to ensure the sustainability of the network. To mitigate undesired power breakdown from the maintenance operations, the objective of the problem is to minimize a stochastic risk function measuring the risk of power grid maintenance schedule. The problem can be formulated as a Mixed Integer Programming (MIP) problem involving many integer variables, which is very challenging to solve. A hybrid mathematical programming-heuristic algorithm is developed to solve large-sized problems, consisting of two phases: The first phase utilizes a simplified MIP formulation with objective perturbation to find feasible solutions quickly. The second phase adapts the simulated-annealing algorithm to improve the solutions. A computation study on the real-life instances shows that the proposed algorithm outperforms Cplex. Especially, the proposed algorithm could find good feasible solutions for all tested instances, while Cplex failed to obtain feasible solutions within three hours.

영어초록

This paper considers a stochastic job allocation problem inspired by a real-life electric power grid operator. The power grid requires regular maintenance to ensure the sustainability of the network. To mitigate undesired power breakdown from the maintenance operations, the objective of the problem is to minimize a stochastic risk function measuring the risk of power grid maintenance schedule. The problem can be formulated as a Mixed Integer Programming (MIP) problem involving many integer variables, which is very challenging to solve. A hybrid mathematical programming-heuristic algorithm is developed to solve large-sized problems, consisting of two phases: The first phase utilizes a simplified MIP formulation with objective perturbation to find feasible solutions quickly. The second phase adapts the simulated-annealing algorithm to improve the solutions. A computation study on the real-life instances shows that the proposed algorithm outperforms Cplex. Especially, the proposed algorithm could find good feasible solutions for all tested instances, while Cplex failed to obtain feasible solutions within three hours.

참고자료

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