Journal Article10.3390/coatings14030368
A Decomposition-Based Multi-Objective Evolutionary Algorithm for Solving Low-Carbon Scheduling of Ship Segment Painting
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TL;DR: A decomposition-based multi-objective evolutionary algorithm for solving low-carbon scheduling of ship segment painting effectively reduces carbon emissions and improves painting efficiency.
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Abstract: Ship painting, as one of the three pillars of the shipping industry, runs through the whole process of ship construction. However, there are low scheduling efficiency and excessive carbon emissions in the segmental painting process, and optimizing the scheduling method is an important means to achieve the sustainable development of the ship manufacturing industry. To this end, firstly, a low-carbon scheduling mathematical model for the segmented painting workshop is proposed, aiming to reduce carbon emissions and improve the painting efficiency of the segmented painting workshop. Second, an artificial bee colony algorithm designed based on a decomposition strategy (MD/ABC) is proposed to solve the model. In the first stage, five neighborhood switching methods are designed to achieve the global search employed for each solution. In the second stage, the Technique of Ordering the Ideal Solutions (TOPSIS) improves the competition mechanism through the co-evolution between neighboring subproblems and designs the angle to define the relationship between neighboring subproblems to enhance the localized search and improve population quality. The solution exchange strategy is used in the third stage to improve the efficiency of the algorithm. In addition, a two-stage coding method is designed according to the characteristics of the scheduling problem. Finally, the algorithm before and after the improvement and with other algorithms is analyzed using comparative numerical experiments. The experimental results show the effectiveness of the algorithm in solving the low-carbon scheduling problem of ship segmental painting and can provide reliable guidance for the scheduling program of segmented painting workshops in shipyards.
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Citations
Correction: Bu et al. A Decomposition-Based Multi-Objective Evolutionary Algorithm for Solving Low-Carbon Scheduling of Ship Segment Painting. Coatings 2024, 14, 368
Abstract: In the original publication [...]
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TL;DR: In this paper, two strategies are included: niche-based density estimation strategy and angle-based selection strategy, which are employed in the environmental selection to eliminate the worst individual from the population in an iterative way.
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Technique for order of preference by similarity to ideal solution (TOPSIS) method for the generation of external preference mapping using rapid sensometric techniques.
Lorena Guadalupe Ramón-Canul,Diana Laura Margarito‐Carrizal,Rogelio Limón‐Rivera,Uriel Alejandro Morales‐Carrrera,Ingrid Mayanin Rodríguez-Buenfil,Manuel Octavio Ramírez-Sucre,Adán Cabal‐Prieto,José Andrés Herrera-Corredor,Emmanuel de Jesús Ramírez-Rivera +8 more
TL;DR: The combination of the TOPSIS technique with rapid sensory techniques is a reliable alternative for the construction of PREFMAPs in order to identify the sensory attributes responsible for preference and rejection of food products.
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