A genetic algorithm for the rectangular packing problem of placement function

2009 ◽  
Author(s):  
Wang Jinmin ◽  
Zhu Yanhua ◽  
Wang Baochun
Keyword(s):  
Genetic Algorithm ◽  
Packing Problem ◽  
Rectangular Packing

Hybrid Genetic Algorithm with Simulated Annealing Based on Best-Fit Strategy for Rectangular Packing Problem

2010 ◽  
Vol 118-120 ◽  
pp. 379-383
Author(s):  
Yu Yu Zhou ◽  
Yun Qing Rao ◽  
Chao Yong Zhang ◽  
Liang Gao
Keyword(s):  
Genetic Algorithm ◽  
Simulated Annealing ◽  
Hybrid Algorithm ◽  
Hybrid Genetic Algorithm ◽  
Packing Problem ◽  
Crossover Operator ◽  
Complete Problems ◽  
Np Complete ◽  
Rectangular Packing ◽  
Best Fit

In this paper we address a rectangular packing problem (RPP), which is one of the most difficult NP-complete problems. Borrowing from the respective advantages of the two algorithms, a hybrid of genetic algorithm (GA) and simulated annealing (SA) is developed to solve the RPP. Firstly, we adopt and improve Burke’s best-fit (BF) placement strategy, which is not restricted to the first shape but may search the list for better candidate shapes for placement. Secondly, we propose a new crossover operator, named Improved Precedence Operation Crossover (IPOX), which can preserve the valuable characteristics of the previous generation. At last, using a new temperature and iterations strategy and Boltzmann-type operator, we propose SA to re-intensify search from the promising solutions. The computational results validate the quality and the effectiveness of hybrid algorithm.

scholarly journals An Improved Adaptive Genetic Algorithm for Two-Dimensional Rectangular Packing Problem

2021 ◽  
Vol 11 (1) ◽  
pp. 413
Author(s):  
Yi-Bo Li ◽  
Hong-Bao Sang ◽  
Xiang Xiong ◽  
Yu-Rou Li
Keyword(s):  
Genetic Algorithm ◽  
Packing Problem ◽  
Global Perspective ◽  
Adaptive Genetic Algorithm ◽  
Two Dimensional ◽  
Filling Rate ◽  
Zero Waste ◽  
Population Evolution ◽  
Rectangular Packing ◽  
The Impact

This paper proposes the hybrid adaptive genetic algorithm (HAGA) as an improved method for solving the NP-hard two-dimensional rectangular packing problem to maximize the filling rate of a rectangular sheet. The packing sequence and rotation state are encoded in a two-stage approach, and the initial population is constructed from random generation by a combination of sorting rules. After using the sort-based method as an improved selection operator for the hybrid adaptive genetic algorithm, the crossover probability and mutation probability are adjusted adaptively according to the joint action of individual fitness from the local perspective and the global perspective of population evolution. The approach not only can obtain differential performance for individuals but also deals with the impact of dynamic changes on population evolution to quickly find a further improved solution. The heuristic placement algorithm decodes the rectangular packing sequence and addresses the two-dimensional rectangular packing problem through continuous iterative optimization. The computational results of a wide range of benchmark instances from zero-waste to non-zero-waste problems show that the HAGA outperforms those of two adaptive genetic algorithms from the related literature. Compared with some recent algorithms, this algorithm, which can be increased by up to 1.6604% for the average filling rate, has great significance for improving the quality of work in fields such as packing and cutting.

A New Effective Hybrid Optimization Strategy for Rectangular Packing Problem

2011 ◽  
Vol 189-193 ◽  
pp. 3131-3136
Author(s):  
Yu Yu Zhou ◽  
Yun Qing Rao ◽  
Chao Yong Zhang ◽  
Guo Jun Zhang
Keyword(s):  
Genetic Algorithm ◽  
Simulated Annealing ◽  
Packing Problem ◽  
Hybrid Optimization ◽  
Optimization Strategy ◽  
Complete Problems ◽  
Np Complete ◽  
Rectangular Packing

In this paper we address a rectangular packing problem (RPP), which is one of the most difficult NP-complete problems. First, greedy biggest space sequencing (GBSS) is presented as a new placement strategy, which is very essential to RPP. Then, borrowing from the respective advantages of the two algorithms, genetic algorithm (GA) and simulated annealing (SA), a hybrid optimization policy is developed. The hybrid GASA is subjected to a test using a set of benchmarks. Compared to other approaches from the literature the hybrid optimization strategy performs better.

An Ordering Approach Based on Evaluative Function for Rectangular Packing Problem

2012 ◽  
Vol 229-231 ◽  
pp. 2197-2200
Author(s):  
Yang Qi ◽  
Jin Min Wang
Keyword(s):  
Packing Problem ◽  
Space Utilization ◽  
Rectangular Packing

The most of the ordering approaches are derived from the practice of the production and life, and these approaches ensure relatively good packing result. In view of rectangular packing problem, this paper presents an ordering approach which is based on evaluative function. By the analysis of this evaluative function, some properties of this ordering approach are obtained. And through contrast experiment, it is proved that this ordering approach is beneficial to improve the space utilization of packing result.

scholarly journals Smart Packing Simulator for 3D Packing Problem Using Genetic Algorithm

2020 ◽  
Vol 1447 ◽  
pp. 012041
Author(s):  
U. Khairuddin ◽  
N. A. Z. M. Razi ◽  
M. S. Z. Abidin ◽  
R. Yusof
Keyword(s):  
Genetic Algorithm ◽  
Packing Problem ◽  
3D Packing
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