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A Parallel Biased Random-Key Genetic Algorithm with Multiple Populations Applied to Irregular Strip Packing Problems

机译:求解不规则条形堆积问题的多种群并行偏置随机密钥遗传算法

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摘要

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 (mu-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 (mu-BRKGA) algorithm, computational tests using benchmark problems were applied, analyzed, and compared with different approaches.
机译:不规则的条带包装问题(ISPP)是一类切割和包装问题(C&P),其中必须将一组具有任意格式的物品放置在具有可变长度的容器中。这项工作的目的是最小化满足给定需求所需的面积。从制造商到出口商(例如造船,服装和玻璃制品),ISPP存在于各种行业中。在本文中,我们采用无碰撞区域(CFR)概念作为定位方法,为ISPP提出了具有多个总体的并行有偏随机密钥遗传算法(mu-BRKGA),以获取高效,快速的布局解。所提出算法的布局问题由在容器中的放置顺序和相应的方向表示。为了评估提出的(mu-BRKGA)算法,使用了基准问题的计算测试得到了应用,分析并与不同方法进行了比较。

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  • 来源
    《Mathematical Problems in Engineering》 |2017年第9期|1670709.1-1670709.11|共11页
  • 作者单位

    Univ Fortaleza UNIFOR, Grad Program Appl Informat, Av Washington Soares,1321 Bl J Sl 30, BR-60811905 Fortaleza, Ceara, Brazil;

    Univ Fortaleza UNIFOR, Grad Program Appl Informat, Av Washington Soares,1321 Bl J Sl 30, BR-60811905 Fortaleza, Ceara, Brazil;

    Univ Fortaleza UNIFOR, Grad Program Appl Informat, Av Washington Soares,1321 Bl J Sl 30, BR-60811905 Fortaleza, Ceara, Brazil;

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