TY - GEN

T1 - An Industry Maintenance Planning Optimization Problem Using CMA-VNS and Its Variations

AU - Zholobova, Anna

AU - Zholobov, Yefim

AU - Polyakov, Ivan

AU - Petrosian, Ovanes

AU - Vlasova, Tatyana

N1 - Publisher Copyright: © 2021, Springer Nature Switzerland AG.

PY - 2021

Y1 - 2021

N2 - In this article, we consider the statement of a problem described in the competition ROADEF/EURO challenge 2020 [4] dedicated to a maintenance planning optimization problem in collaboration with RTE [5]. First of all, the main task is to build an optimal maintenance schedule for a high voltage transmission network to ensure the delivery and supply of electricity. To solve this problem we use several optimization methods to find the best possible maintenance schedule that would be consistent with all work-related constraints and would take into account the risk assessment. There are many existing heuristic, metaheuristic, and exact algorithms that can solve this optimization problem; yet it is highly feasible that the state-of-the-art methods currently available may offer some improvement. For this reason, taking into account the task at hand, we decided to use the CMA-VNS [27] algorithm after examining the results of the Combinatorial Black Box Optimization Competition [2]. The algorithm is hybrid and consists of Bipop CMA-ES and VNS algorithms that make it possible to obtain solutions with a zero penalty function and close to a minimal objective function in an admissible time. Other popular algorithms were carried out in comparison with our solution to prove the efficiency of this approach. The effectiveness of this approach to solving the problem is demonstrated.

AB - In this article, we consider the statement of a problem described in the competition ROADEF/EURO challenge 2020 [4] dedicated to a maintenance planning optimization problem in collaboration with RTE [5]. First of all, the main task is to build an optimal maintenance schedule for a high voltage transmission network to ensure the delivery and supply of electricity. To solve this problem we use several optimization methods to find the best possible maintenance schedule that would be consistent with all work-related constraints and would take into account the risk assessment. There are many existing heuristic, metaheuristic, and exact algorithms that can solve this optimization problem; yet it is highly feasible that the state-of-the-art methods currently available may offer some improvement. For this reason, taking into account the task at hand, we decided to use the CMA-VNS [27] algorithm after examining the results of the Combinatorial Black Box Optimization Competition [2]. The algorithm is hybrid and consists of Bipop CMA-ES and VNS algorithms that make it possible to obtain solutions with a zero penalty function and close to a minimal objective function in an admissible time. Other popular algorithms were carried out in comparison with our solution to prove the efficiency of this approach. The effectiveness of this approach to solving the problem is demonstrated.

KW - Global optimization

KW - Large scale combinatorial optimization

KW - Maintenance planning

KW - Operations research

UR - http://www.scopus.com/inward/record.url?scp=85115874622&partnerID=8YFLogxK

U2 - 10.1007/978-3-030-86433-0_30

DO - 10.1007/978-3-030-86433-0_30

M3 - Conference contribution

AN - SCOPUS:85115874622

SN - 9783030864323

T3 - Communications in Computer and Information Science

SP - 429

EP - 443

BT - Mathematical Optimization Theory and Operations Research: Recent Trends

A2 - Strekalovsky, Alexander

A2 - Kochetov, Yury

A2 - Gruzdeva, Tatiana

A2 - Orlov, Andrei

PB - Springer Nature

T2 - 20th International Conference on Mathematical Optimization Theory and Operations Research , MOTOR 2021

Y2 - 5 July 2021 through 10 July 2021

ER -