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Simplified swarm optimization for cutting optimization problems
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AI
DOI：10.1016/j.engappai.2025.113284.png)
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Abstract
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This study investigates the cutting optimization problem proposed by Saint-Gobain France, a building material manufacturer, in the 2018 French Operational Research and Decision Support Society (ROADEF ) and the European Operational Research Society (EURO) (2018 ROADEF/EURO) Applied Optimization Problem Challenge. This problem involves a two-dimensional, three-stage cutting process with special constraints that prevent standard cutting algorithms from being applied directly. Previous research has explored the cutting problem for raw materials using methods such as exact algorithms, heuristic algorithms, and metaheuristic algorithms. This study applies the implemented Artificial intelligence (AI), as well as the application of AI based on Simplified Swarm Optimization (SSO) algorithm's single-variable update method to solve the problem, ensuring that the updated solution meets the problem's constraints. Furthermore, this study proposes using vertical and horizontal lines to record the item placement positions. The experimental results show that, among 50 datasets, the method proposed in this study achieves superior solution quality compared to other algorithms.
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