模拟退火排样

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二维排样问题

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The two-dimensional cutting stock problem, also known as the two-dimensional packing problem, is a mathematical problem that involves cutting rectangles from a larger rectangle with the objective of minimizing waste. It is a classic optimization problem that has applications in many fields, including manufacturing, logistics, and engineering. The problem is NP-hard, which means that finding an optimal solution can be computationally expensive, particularly when the number of items to be cut is large. There are several algorithms that have been developed to solve the problem, including exact methods, heuristics, and metaheuristics. Some of the most popular algorithms include branch and bound, simulated annealing, and genetic algorithms. Despite the computational challenges involved, the two-dimensional cutting stock problem remains an important area of research due to its practical applications and its relevance to many real-world problems.