کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
1134530 956072 2011 10 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
On the concept of density control and its application to a hybrid optimization framework: Investigation into cutting problems
موضوعات مرتبط
مهندسی و علوم پایه سایر رشته های مهندسی مهندسی صنعتی و تولید
پیش نمایش صفحه اول مقاله
On the concept of density control and its application to a hybrid optimization framework: Investigation into cutting problems
چکیده انگلیسی

The Generate-and-Solve (GS) methodology is a hybrid approach that combines a metaheuristic component with an exact solver. GS has been recently introduced in the literature in order to solve cutting and packing problems, showing promising results. The GS framework includes a metaheuristic engine (e.g., a genetic algorithm) that works as a generator of reduced instances of the original optimization problem, which are, in turn, formulated as mathematical programming problems and solved by an integer programming solver. In this paper, we present an extended version of GS, focusing primarily on the concept of a new Density Control Operator (DCO). The role of this operator is to adaptively control the dimension of the reduced instances in such a way as to allow a much steadier progress towards a better solution, thereby avoiding premature convergence. In order to assess the potentials of this novel version of the GS methodology, we conducted computational experiments on a set of difficult benchmark instances of the constrained non-guillotine cutting problem. The results achieved are quantitatively and qualitatively discussed in terms of effectiveness and efficiency, showing that the proposed variant of the GS hybridization framework is highly suitable when effectiveness is a major requirement.


► Generate-and-Solve (GS) is a recently-proposed hybrid optimization approach.
► We present an extended version of GS, based on a new Density Control Operator (DCO).
► DCO adaptively controls the size of reduced problem instances along the search.
► We conducted tests on hard constrained non-guillotine cutting problem instances.
► The new GS variant shows high effectiveness in locating (quasi-)optimal solutions.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computers & Industrial Engineering - Volume 61, Issue 3, October 2011, Pages 463–472
نویسندگان
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