A beam search algorithm for the circular packing problem

2009 ◽  
Vol 36 (5) ◽  
pp. 1513-1528 ◽  
Author(s):  
Hakim Akeb ◽  
Mhand Hifi ◽  
Rym M’Hallah
Keyword(s):  
Search Algorithm ◽  
Packing Problem ◽  
Beam Search ◽  
Circular Packing

scholarly journals Hybridizing Beam Search with Tabu Search for the Irregular Packing Problem

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Yunqing Rao ◽  
Peng Wang ◽  
Qiang Luo
Keyword(s):  
Tabu Search ◽  
Hybrid Algorithm ◽  
Numerical Experiments ◽  
Search Algorithm ◽  
Packing Problem ◽  
Benchmark Problems ◽  
Beam Search ◽  
Hybrid Search

The irregular packing problem involves arranging all the irregular pieces on a plate with the objective of maximizing the use of material. In this article, the layout is formed by the ordered sequence of the irregular pieces which is obtained by a hybrid search algorithm and where the order is decoded by a proposed placement principle. First, a novel no-fit-polygon (NFP) generator is introduced. Then, a placement principle is presented with the new NFP generator. Finally, a search algorithm hybridized with beam search (BS) and tabu search (TS) is proposed to search over the sequence. The numerical experiments with many benchmark problems show that the hybrid algorithm is an applicative and effective approach for solving the irregular packing problem. The hybrid algorithm can produce competitive solutions in less time than many other typical algorithms.

A Reinforced Tabu Search Approach for 2D Strip Packing

2012 ◽  
pp. 171-188
Author(s):  
Giglia Gómez-Villouta ◽  
Jean-Philippe Hamiez ◽  
Jin-Kao Hao
Keyword(s):  
Tabu Search ◽  
Search Algorithm ◽  
Fitness Function ◽  
Packing Problem ◽  
Two Dimensional ◽  
Strip Packing ◽  
Benchmark Instances ◽  
Finite Set ◽  
Infinite Height ◽  
Search Approach

This paper discusses a particular “packing” problem, namely the two dimensional strip packing problem, where a finite set of objects have to be located in a strip of fixed width and infinite height. The variant studied considers regular items, rectangular to be precise, that must be packed without overlap, not allowing rotations. The objective is to minimize the height of the resulting packing. In this regard, the authors present a local search algorithm based on the well-known tabu search metaheuristic. Two important components of the presented tabu search strategy are reinforced in attempting to include problem knowledge. The fitness function incorporates a measure related to the empty spaces, while the diversification relies on a set of historically “frozen” objects. The resulting reinforced tabu search approach is evaluated on a set of well-known hard benchmark instances and compared with state-of-the-art algorithms.

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