![]() ![]() The typology of C&P problems introduced by Dyckhoff initially provided an excellent instrument for the organisation and categorisation of existing and new literature. ![]() The number of publications in the area of Cutting and Packing (C&P) has increased considerably over the last two decades. They are required to provide good, but not necessarily optimal Heuristic methods have greater flexibility in taking into account problem- specific constraints and offer a good trade-off between the quality of a solution and its computational effort. ![]() There are two main approaches to solve this problem: exact and heuristic methods. This means that all algorithms currently known for finding optimal solutions require a number of computational steps that may grow exponentially with the problem size rather than according to a polynomial function. These problems, with all their extensions and variants, are well known to be NP-hard (1). Generally speaking, CSP are optimization problems consisting of placing a given set of small objects, called items, into a given set of larger ones, called stock sheets, usually with the objective of reducing the waste to a minimum. Therefore, this comparison was based on some of the packages' main features, the most relevant to the problem's context. Cutting stock problems (CSP) may involve a variety of objectives and constraints, which directly depend on technological and organizational parameters of each company. We present a detailed survey of software packages for two-dimensional cutting stock problems.
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