Parameter Analysis of Placement Function for the Rectangular Packing Problem Based on GA

2016 ◽  
Vol 836-837 ◽  
pp. 381-386
Author(s):  
Yan Hua Zhu

Rectangle part is the foundation of irregular part layout, about which domestic and overseas scholars have studied a lot and have put forward many algorithms. Based on a careful study of these algorithms in the paper, it is determined to solve the rectangle packing problem with genetic algorithm analysis. Different from the formerly used the genetic algorithm optimization layout, the algorithm of this paper stresses optimization localization rule in order to solve layout problem with the advantages of global searching ability of genetic algorithm. This algorithm sets the utilization ratio of the maximum area of capacity as the goal, after confirming the priority of deposition sequence of rectangle, in view of the locating rule of rectangle packing, based on feasible region and by introducing the method of attractive factors, optimizing the calculation for each parameter of placement function by utilizing genetic algorithm.Positioning function of the structure of this paper by changing the parameter value can cover the previous golden horn strategy, the lower left corner strategy, down the steps such as positioning method. Use VC programming to realize automatic two dimensional rectangular layout systems, the algorithm and example verification, the precision of parameter on the result of layout, the number of attractor for layout results, and the influence of parameter values for different rectangular piece of regularity. According to different rectangular block configuration, layout scheme can be better and faster.

2017 ◽  
Vol 2017 ◽  
pp. 1-11 ◽  
Author(s):  
Bonfim Amaro Júnior ◽  
Plácido Rogério Pinheiro ◽  
Pedro Veras Coelho

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.


2018 ◽  
Vol 03 (02) ◽  
pp. 1850009 ◽  
Author(s):  
Amandeep Kaur Virk ◽  
Kawaljeet Singh

This paper applies cuckoo search and bat metaheuristic algorithms to solve two-dimensional non-guillotine rectangle packing problem. These algorithms have not been found to be used before in the literature to solve this important industrial problem. The purpose of this work is to explore the potential of these new metaheuristic methods and to check whether they can contribute in enhancing the performance of this problem. Standard benchmark test data has been used to solve the problem. The performance of these algorithms was measured and compared with genetic algorithm and tabu search techniques which can be found to be used widely in the literature to solve this problem. Good optimal solutions were obtained from all the techniques and the new metaheuristic algorithms performed better than genetic algorithm and tabu search. It was seen that cuckoo search algorithm excels in performance as compared to the other techniques.


2007 ◽  
Vol 13 (1s) ◽  
pp. 33-37
Author(s):  
V. Makarenko ◽  
◽  
G. Ruecker ◽  
R. Sommer ◽  
N. Djanibekov ◽  
...  

Sign in / Sign up

Export Citation Format

Share Document