Development of the Multimethod Genetic Algorithm for the Strip Packing Problem

2014 ◽  
Vol 598 ◽  
pp. 377-381 ◽  
Author(s):  
Vladislav A. Chekanin ◽  
Alexander V. Chekanin
Keyword(s):  
Genetic Algorithm ◽  
Packing Problem ◽  
Strong Sense ◽  
Np Hard ◽  
Two Dimensional ◽  
Strip Packing ◽  
Packing Problems ◽  
Total Length

The actual in industry strip packing problem which is NP-hard in strong sense is considered in paper. To the strip packing problem comes down solution of a large number of different practical problems, including problems in logistics, scheduling and planning. The new heuristics intended to pack a given set of rectangular two-dimensional objects in order to minimize of the total length of the filled part of container with an infinity length and fixed width are offered. The proposed multimethod genetic algorithm is investigated on well-known standard benchmarks of two-dimensional strip packing problems.

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

2017 ◽  
Vol 2017 ◽  
pp. 1-11 ◽  
Author(s):  
Bonfim Amaro Júnior ◽  
Plácido Rogério Pinheiro ◽  
Pedro Veras Coelho
Keyword(s):  
Genetic Algorithm ◽  
Packing Problem ◽  
Benchmark Problems ◽  
Strip Packing ◽  
Layout Problem ◽  
Multiple Populations ◽  
Packing Problems ◽  
Free Region ◽  
Positioning Method ◽  
The Given

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.

Effective Data Structure for the Multidimensional Orthogonal Bin Packing Problems

2014 ◽  
Vol 962-965 ◽  
pp. 2868-2871 ◽  
Author(s):  
Alexander V. Chekanin ◽  
Vladislav A. Chekanin
Keyword(s):  
Data Structure ◽  
Linked Data ◽  
Bin Packing ◽  
High Efficiency ◽  
Optimization Problems ◽  
Packing Problem ◽  
Strong Sense ◽  
Np Hard ◽  
Packing Problems ◽  
Orthogonal Packing Problem

The actual in industry multidimensional orthogonal packing problem is considered in the article. Solution of a large number of different practical optimization problems, including resources saving problem, optimization problems in logistics, scheduling and planning comes down to the orthogonal packing problem which is NP-hard in strong sense. One of the indicators characterizing the efficiency of packing constructing algorithm is the efficiency of the used data structure. In the article a multilevel linked data structure that increases the speed of constructing of a packing is proposed. The carried out computational experiments show the high efficiency of the new data structure. Multilevel linked data structure is applicable for multidimensional orthogonal bin packing problems any kind.

scholarly journals Dealing with Nonregular Shapes Packing

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Bonfim Amaro Júnior ◽  
Plácido Rogério Pinheiro ◽  
Rommel Dias Saraiva ◽  
Pedro Gabriel Calíope Dantas Pinheiro
Keyword(s):  
Genetic Algorithm ◽  
Case Studies ◽  
Textile Industry ◽  
Packing Problem ◽  
Benchmark Problems ◽  
Practical Case ◽  
Two Dimensional ◽  
Cutting And Packing ◽  
Strip Packing ◽  
Bottom Left

This paper addresses the irregular strip packing problem, a particular two-dimensional cutting and packing problem in which convex/nonconvex shapes (polygons) have to be packed onto a single rectangular object. We propose an approach that prescribes the integration of a metaheuristic engine (i.e., genetic algorithm) and a placement rule (i.e., greedy bottom-left). Moreover, a shrinking algorithm is encapsulated into the metaheuristic engine to improve good quality solutions. To accomplish this task, we propose a no-fit polygon based heuristic that shifts polygons closer to each other. Computational experiments performed on standard benchmark problems, as well as practical case studies developed in the ambit of a large textile industry, are also reported and discussed here in order to testify the potentialities of proposed approach.

A biased random-key genetic algorithm using dotted board model for solving two-dimensional irregular strip packing problems

2020 ◽  
Author(s):  
Bonfim Amaro Junior ◽  
Rodrigo Lima da Costa ◽  
Placido Rogerio Pinheiro ◽  
Luiz Jonata Pires de Araujo ◽  
Alexandr Grichshenko
Keyword(s):  
Genetic Algorithm ◽  
Two Dimensional ◽  
Strip Packing ◽  
Packing Problems

Two-Dimensional Packing Problems Using Genetic Algorithms

1996 ◽  
Author(s):  
Sakait Jain ◽  
Hae Chang Gea
Keyword(s):  
Genetic Algorithm ◽  
Genetic Algorithms ◽  
Finite Number ◽  
Packing Problem ◽  
Two Dimensional ◽  
Connectivity Analysis ◽  
Packing Problems ◽  
The Creation ◽  
New Feature ◽  
Number Of Cells

Abstract This paper presents a technique for applying genetic algorithms for the two dimensional packing problem. The approach is applicable to not only convex shaped objects, but, can also accommodate any type of concave and complex shaped objects including objects with holes. In this approach, a new concept of a two dimensional genetic chromosome is introduced. The total layout space is divided into a finite number of cells for mapping it into this 2-D genetic algorithm chromosome. The mutation and crossover operators have been modified and are applied in conjunction with connectivity analysis for the objects to reduce the creation of faulty generations. A new feature has been added to the genetic algorithm(GA) in the form of a new operator called compaction. Several examples of GA based layout are presented.

scholarly journals A SAT-based Method for Solving the Two-dimensional Strip Packing Problem

2010 ◽  
Vol 102 (3-4) ◽  
pp. 467-487 ◽  
Author(s):  
Takehide Soh ◽  
Katsumi Inoue ◽  
Naoyuki Tamura ◽  
Mutsunori Banbara ◽  
Hidetomo Nabeshima
Keyword(s):  
Packing Problem ◽  
Two Dimensional ◽  
Strip Packing
Sign in / Sign up

Export Citation Format

Share Document