Ballast Water Dynamic Allocation Optimization for Revolving Floating Cranes Based on a Hybrid Algorithm of Fuzzy-Particle Swarm Optimization with Domain Knowledge

Abstract

Ballast systems and ballast water dynamic allocation between ballast tanks are very important for ensuring the offshore operation efficiency and safety of the revolving floating crane (RFC). Its modeling and solving have multiple difficulties such as modeling complexity, solving complexity and engineering practicability. Early studies showed that domain knowledge is of great significance for the optimization of the design quality and innovation of such complex engineering issues. By analyzing the coupled operation process characteristics among the floating crane, ship hull and ballast system, a ballast water allocation optimization model based on dynamic programming strategy is established. The domain knowledge of ship ballasting is extracted, and a domain knowledge base of expert experience rules for the ballast water allocation is established. A Fuzzy-Particle Swarm Optimization (FPSO) algorithm is given to obtain the optimal allocation scheme, which uses fuzzy logic inference to process domain knowledge and improve the solving quality. Three different cases are given to illustrate the validity of the proposed model and algorithm by comparing it with other algorithms. The analysis results show that the established optimization method can effectively improve the operation efficiency and reduce the calculation time and the number of ballast tanks involved in allocation, which makes the optimal scheme more suitable for engineering applications.

Point-to-Point-Based Optimization Method of Ballast Water Allocation for Revolving Floating Cranes with Experimental Verification

“…Long [3] introduced an improved genetic algorithm to optimize the allocation of ballast water in barges, with results indicating that the improved genetic algorithm has a shorter computation time and higher efficiency. Liu et al [4] proposed an optimization scheme based on the fuzzy particle swarm optimization algorithm for the ballast-allocation problem, and their comparative results demonstrated the advantages of this method in terms of efficiency improvement, reduced computation time, and good applicability. Topalov et al [5] developed an information system for the real-time acquisition of the operational parameters of the ballast system, and the research results confirmed the effectiveness of this information system for realizing the automatic allocation of ballast water.…”

Online and Offline Model for Housekeeping Order Assignment Based on Dynamic Programming Algorithm

“…In the case of high repurchase motivation driven (HRMD) and medium repurchase motivation driven (MRMD) methods, an improved linear time complexity simulated annealing (SA) algorithm was used to solve the NP hard assignment problem. Liu et al [22] proposed a fuzzy particle swarm optimization (FPSO) algorithm, which uses fuzzy logic reasoning to process domain knowledge, improve the solution quality, and obtain the optimal allocation scheme. By comparing with other algorithms, three different examples were provided to demonstrate the effectiveness of the proposed model and algorithm.…”