Offshore engineering construction projects are large and complex, having the characteristics of multiple execution modes and multiple resource constraints. Their complex internal scheduling processes can be regarded as resourceconstrained project scheduling problems (RCPSPs). To solve RCPSP problems in offshore engineering construction more rapidly, a hybrid genetic algorithm was established. To solve the defects of genetic algorithms, which easily fall into the local optimal solution, a local search operation was added to a genetic algorithm to defend the offspring after crossover/mutation. Then, an elitist strategy and adaptive operators were adopted to protect the generated optimal solutions, reduce the computation time and avoid premature convergence. A calibrated function method was used to cater to the roulette rules, and appropriate rules for encoding, decoding and crossover/mutation were designed. Finally, a simple network was designed and validated using the case study of a real offshore project. The performance of the genetic algorithm and a simulated annealing algorithm was compared to validate the feasibility and effectiveness of the approach.

Quality traceability plays an essential role in assembling and welding offshore platform blocks. The improvement of the welding quality traceability system is conducive to improving the durability of the offshore platform and the process level of the offshore industry. Currently, quality management remains in the era of primary information, and there is a lack of effective tracking and recording of welding quality data. When welding defects are encountered, it is difficult to rapidly and accurately determine the root cause of the problem from various complexities and scattered quality data. In this paper, a composite welding quality traceability model for offshore platform block construction process is proposed, it contains the quality early-warning method based on long short-term memory and quality data backtracking query optimization algorithm. By fulfilling the training of the early-warning model and the implementation of the query optimization algorithm, the quality traceability model has the ability to assist enterprises in realizing the rapid identification and positioning of quality problems. Furthermore, the model and the quality traceability algorithm are checked by cases in actual working conditions. Verification analyses suggest that the proposed early-warning model for welding quality and the algorithm for optimizing backtracking requests are effective and can be applied to the actual construction process.

Aimed at enhancing the effectiveness and efficiency for offshore platform project scheduling, a multiagent collaborative scheduling model based on the analysis of distributed offshore platform project scheduling was proposed. The functional definitions and internal structure of agents in the proposed system were analyzed. Moreover, in order to explore the cooperative way of agents, communication mechanism was presented and a negotiation model was elaborated. Then, system architecture and hardware architecture were constructed to lay a foundation to develop the collaborative scheduling system. Finally, an intelligent algorithm based on Bayesian method was designed to verify the negotiation model and a prototype system was developed to test the feasibility and rationality.

Since task allocation is one of the core tasks of ship design, the choice of its allocation strategy is a key factor that affects whether the task and the design agent can be beneficially matched. Different from the traditional one-way assignment mode of assigning tasks to designers, in the task assignment strategy of modern ship collaborative design mode, designers’ ability and benefit ratio is getting higher and higher. Therefore, in order to improve the efficiency and quality of task design, this paper proposes a multidesign agent-task allocation decision-making method. In this paper, the task attributes and designers’ attributes are introduced into the task allocation strategy model, and the fuzzy linguistic variable method is used to build the evaluation index matrix of the design agent, and the task timeliness function is established. Secondly, the multidesign agent-task benefit function is established and solved to obtain the best allocation strategy. Finally, through example verification and comparative analysis with the Round-Robin algorithm (RR) and the Weighted Round-Robin (WRR) algorithm, the validity, feasibility, and stability of the multidesign agent-task allocation decision-making method proposed in this paper are verified, and it is proved that the task allocation method takes the bilateral needs of the task and the design agent into account, solves the optimal allocation strategy of collaborative design tasks, and realizes the balanced allocation between the ship collaborative design task and the design agent.

In order to complete the offshore platform project scheduling intelligently, an improved scheduling optimization system based on the parallel genetic algorithm was proposed. An optimal model for the large‐scale offshore platform project scheduling problem (LSOPPSP) was built and produced the mathematic model of LSOPPSP, based on the characteristics of the abundance of activities, long duration, high uncertainty, and frequent changes. In long‐term unsteady manufacturing, this model can provide good robustness. In addition, the essential steps of the multitime window parallel genetic algorithm were proposed. An improved population initialization algorithm was designed, as well as the coevolution strategy among populations was also proposed in parallel computing. These two strategies can increase population variety while also speeding up convergence. Finally, the suggested parallel scheduling system was deployed in our self‐developed schedule optimization software for offshore platform enterprises, and the outperformance of the improved algorithm was proven by simulated examples and practical application.

The development of the cruise industry is an important part of the country’s “Marine power” and “One Belt, One Road” strategy. Improving the independent construction of cruise ships is of great significance to my country’s economic and social development. Aiming at the problem of the assembly order of cruise ship outfitting parts are many, the quantity is large, and the interchangeability of materials is higher than that of conventional ships, a cruise ship outfitting on-board assembly scheduling problem model is constructed, and a cruise ship outfitting on-board assembly material scheduling method oriented to generally outfitting is proposed. The improved genetic algorithm is used to dispatch the materials on the outfitting ships to realize the optimal utilization of the materials and materials, and the effectiveness of the method is proved by the example verification.