a parallel biased random-key genetic algorithm with multiple populations applied to irregular strip packing problems

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ID: 223167
2017
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Abstract
The irregular strip packing problem (ISPP) is a class of cutting and packing problem (C&P) in which a set of items with arbitrary formats must be placed in a container with a variable length. The aim of this work is to minimize the area needed to accommodate the given demand. ISPP is present in various types of industries from manufacturers to exporters (e.g., shipbuilding, clothes, and glass). In this paper, we propose a parallel Biased Random-Key Genetic Algorithm (µ-BRKGA) with multiple populations for the ISPP by applying a collision-free region (CFR) concept as the positioning method, in order to obtain an efficient and fast layout solution. The layout problem for the proposed algorithm is represented by the placement order into the container and the corresponding orientation. In order to evaluate the proposed (µ-BRKGA) algorithm, computational tests using benchmark problems were applied, analyzed, and compared with different approaches.
Reference Key
jnior2017mathematicala Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors ;Bonfim Amaro Júnior;Plácido Rogério Pinheiro;Pedro Veras Coelho
Journal journal of power sources
Year 2017
DOI
10.1155/2017/1670709
URL
http://dx.doi.org/10.1155/2017/1670709
Keywords
civil engineering (general)mathematics engineering (general)

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