A Continuous Space Location Model and a Particle Swarm Optimization-Based Heuristic Algorithm for Maximizing the Allocation of Ocean-Moored Buoys

Ocean-moored buoys play an important role in global ocean environment monitoring. Motivated by building a sustainable buoy observational network, spatial optimization approach is proposed to site stations maximize monitoring efficiency (SME). To achieve this goal, non-linear, continuous maximum coverage location model named CMCP-Ocean was established, associated with measurement method of the SME. Meanwhile, heuristic framework based on particle swarm (PSO) algorithm built solve model, and strategies including multi-core parallel computing strategy, velocity updating strategy matching, two potential station selection related centroid-based random radiation (CRRM) grid division (RGDM) were established improve performance. The effectiveness PSO-based verified series experiments; schema PSO-for-CMCP-Ocean has also proven be practical efficient. Finally, applied water mass Laizhou Bay China, multi-scale planning solution reported.