A model of multi-objective route optimization for a vessel in drifting ice

Zvyagina, Tatiana; Zvyagin, Petr

doi:10.1016/j.ress.2021.108147

Cited by 17 publications

(5 citation statements)

References 48 publications

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“…In this section, a route planning simulation using the A* algorithm is performed. Detailed explanations of this algorithm can be found in [30][31][32][33][34]. The environmental data used for risk assessment and route planning include ice thickness, ice concentration, and water depth.…”

Section: Environment Data and Design Variablesmentioning

confidence: 99%

Route Planning of a Polar Cruise Ship Based on the Experimental Prediction of Propulsion Performance in Ice

Huang,

Sun,

Sun

et al. 2023

JMSE

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The effective assessment of risk and speed limitations in ice are critical for the route planning of polar cruise ships. While the Polar Operational Limit Assessment Risk Indexing System (POLARIS) is widely used to evaluate the operational risk in ice, its scope of assessment is limited to the ship’s assigned ice class. For a specific ship with a given ice class, the propulsion performance under varying ice conditions is more essential for assessing the besetting risk and finding an optimal route. To establish a more detailed risk evaluation method for a PC6 class polar cruise ship, propulsion performance under various ice conditions is obtained via model tests in an ice tank. During the tests, the tow force, propeller torque, and thrust are measured under different ship velocities and propeller rotation rates, and the relations between required delivered power (P) and ship velocity (V) under the tested ice thicknesses and concentrations are obtained and extended to other ice conditions by curve fitting. A new risk index outcome, RIO*, is proposed after POLARIS according to the optimized load ranges of the ship’s rated power. Four risk levels, including low, medium, high, and unnavigable, are classified with the required propulsion power in ice being 50%, 85%, 100%, and >100% of the rated power, respectively. The recommended speed limit for each risk level is proposed based on the economical service speed of 11 kn, the operational limit of 3 kn by POLARIS and the minimum speed of 0.5 kn to avoid besetting, respectively. Based on the RIO* and P–V relations, the speed map for varying ice thicknesses and concentrations can be calculated. On these bases, a route planning simulation for the present polar cruise ship is performed. Results of the case study show that 29% of the simulated area is identified as “unnavigable” by the present procedure, while only 8% is detected by POLARIS.

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Section: Environment Data and Design Variablesmentioning

confidence: 99%

Route Planning of a Polar Cruise Ship Based on the Experimental Prediction of Propulsion Performance in Ice

Huang,

Sun,

Sun

et al. 2023

JMSE

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“…To find the compromise among conflicting objectives, the Pareto-optimal set of routes was made by solving multiobjective optimization problems; for example, routing optimization was proposed with the drifting ice in ref. [8] and the customized constraints in ref. [9].…”

Section: Introductionmentioning

confidence: 99%

Path-following and collision-avoidance guidance of unmanned sailboats based on beetle antennae search optimization

Deng

Zhang

et al. 2023

Robotica

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There are few studies on the intelligent guidance of unmanned sailboats, which should coordinate pluralistic tasks at sea in the nature of its maneuvring intractability. To ensure the algorithmic practicability, this paper proposes a path-following and collision-avoidance guidance approach of unmanned sailboats with total formulaic description. The risk-detecting mechanism is fabricated by setting a circular detecting zone and using the time to the closest point of approach. Then, the risk of collision, the path deviation, the speed loss, and the course loss can be judged by constructing the cost functions and applying the distance to closest point of approach. The optimized heading angle is deemed as the one minimizing the aggregate cost functions, which is sought by applying and improving the beetle antennae search (BAS) algorithm. In the proposed modified BAS, the searching step is redesigned to enhance the searching efficiency. To ensure the convergence of the real heading angle to the reference, the backstepping-based control law is fabricated for the high-order sailboat model and in the linear form. The control parameters are offline optimized through the modified BAS. Compared with the adaptive control, this controller can guarantee more computation simplicity and the optimized control performance. Finally, simulation corroborates that the sailboat can successfully complete path following and collision avoidance while encountering multiple static and moving obstacles under the proposed schemes.

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“…In cognitive radio system, spectrum sensing technology is a very important link, it is the key to cognitive radio technology. As cognitive radio technology develops, some new spectrum sensing algorithms have been proposed, but these algorithms have the problems of low sensing probability, poor detection accuracy, high false alarm probability, and high computational complexity [3][4]. Using multi-objective optimization theory and fuzzy integral method, a spectrum sensing algorithm is proposed [5][6].…”

Section: Introductionmentioning

confidence: 99%

“…However, in practical application, due to certain constraint relationships between groups, the target value cannot always be constant, which makes the calculation result deviate greatly from the actual situation [16]. The evolutionary gradient under each target is shown in formula (3).…”

mentioning

confidence: 99%

Spectrum Sensing Algorithm by Multi-Objective Optimization Theory and Fuzzy Integral Method

Dong

2023

IEEE Access

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As spectrum resources become increasingly scarce, efficient spectrum management is crucial in wireless communication. To address this challenge, a new spectrum sensing algorithm based on multi-objective optimization theory and fuzzy integral method has been developed. This innovative algorithm combines the whale algorithm and fuzzy integral algorithm, allowing for multi-objective optimization and interference decision-making. It overcomes limitations in existing multi-user spectrum sensing methods, such as low perception probability, poor detection accuracy, high false alarm probability, and computational complexity. Comparative studies show that the multi-objective whale algorithm achieves excellent optimization performance and fast convergence, reaching a throughput of 16.8 after 600 cycles. The collaborative spectrum sensing method, especially the one based on fuzzy integration, performs exceptionally well, particularly in high signal-to-noise ratio environments. This algorithm has significant application potential and effectively addresses spectrum resource management in wireless communication. It offers benefits such as improved spectrum utilization efficiency, scalability, and practicality, making valuable contributions to technological progress and efficiency enhancement in the field.

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A model of multi-objective route optimization for a vessel in drifting ice

Cited by 17 publications

References 48 publications

Route Planning of a Polar Cruise Ship Based on the Experimental Prediction of Propulsion Performance in Ice

Route Planning of a Polar Cruise Ship Based on the Experimental Prediction of Propulsion Performance in Ice

Path-following and collision-avoidance guidance of unmanned sailboats based on beetle antennae search optimization

Spectrum Sensing Algorithm by Multi-Objective Optimization Theory and Fuzzy Integral Method

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