A hybrid heuristic optimization of maintenance routing and scheduling for offshore wind farms

Abstract As the operation and maintenance (O&M) costs constitute a substantial portion of the overall life-cycle cost of offshore wind farms, routing, and scheduling of maintenance are very important for cost reduction. With the multi-type of vessels, multi-period, multi-base of O&M, multi-wind farm and uncertain weather conditions, the optimization of O&M cost is more challenging. In this article, a hybrid heuristic optimization of maintenance routing and scheduling for offshore wind farms is proposed. First, with the maintenance service protocol, mixed particle swarm optimization (MPSO) is applied to seek a desired mapping relation between vessels and wind farms. Utilizing the formalized rules, an optimal vessel allocation scheme is explored in the large solution space by individual crossover, swarm crossover and mutation. Then, with the scheme of vessel allocation, a discrete wolf pack search (DWPS) is introduced to optimize the maintenance route under all constraints. As the evaluation standard of MPSO, the purpose of DWPS is to search the solution space with depth and breadth balanced and find the optimal and open maintenance route with multiple round trips to bases that minimize O&M costs, including travel, technician and penalty costs. Finally, computational experiments and analysis are carried out. The results provide both the optimized cost and detailed arrangements, which can be directly used in the maintenance schedule.