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Autoclave molding scheduling in aerospace composite materials production using an extended whale optimization algorithm.

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Title: Autoclave molding scheduling in aerospace composite materials production using an extended whale optimization algorithm.
Authors: Xu, Huifen1 (AUTHOR), Xie, Naiming1 (AUTHOR) xienaiming@nuaa.edu.cn
Source: Engineering Optimization. May2026, Vol. 58 Issue 5, p1548-1572. 25p.
Subjects: Scheduling, Autoclaves, Metaheuristic algorithms, Simulated annealing, Fiber-reinforced plastics, Batch processing, Bin packing problem
Abstract: Bottlenecks in autoclave molding significantly hinder an enterprise's delivery capacity, resulting in an imbalance between production and demand. This article aims to provide a scheduling solution for autoclave molding to enhance delivery capabilities. A single batch processing machine scheduling model with two-dimensional bin packing constraints is proposed to capture the spatial constraints of jobs within the autoclave. The model also incorporates job release dates and time windows, ensuring that each job is processed within its specified timeframe to meet strict temporal constraints. To solve this model, an extended whale optimization algorithm with a best fit heuristic-based initialization method is developed, incorporating Lévy flight and a simulated annealing mechanism to enhance global exploration and local exploitation. The proposed algorithm is tested on various problem instances and a real-world case, confirming the effectiveness of its mechanisms and demonstrating significant outperformance compared to other baseline algorithms in solving the proposed model. [ABSTRACT FROM AUTHOR]
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Database: Engineering Source
Description
Abstract:Bottlenecks in autoclave molding significantly hinder an enterprise's delivery capacity, resulting in an imbalance between production and demand. This article aims to provide a scheduling solution for autoclave molding to enhance delivery capabilities. A single batch processing machine scheduling model with two-dimensional bin packing constraints is proposed to capture the spatial constraints of jobs within the autoclave. The model also incorporates job release dates and time windows, ensuring that each job is processed within its specified timeframe to meet strict temporal constraints. To solve this model, an extended whale optimization algorithm with a best fit heuristic-based initialization method is developed, incorporating Lévy flight and a simulated annealing mechanism to enhance global exploration and local exploitation. The proposed algorithm is tested on various problem instances and a real-world case, confirming the effectiveness of its mechanisms and demonstrating significant outperformance compared to other baseline algorithms in solving the proposed model. [ABSTRACT FROM AUTHOR]
ISSN:0305215X
DOI:10.1080/0305215X.2025.2517722