Journal Article10.1007/BF01215974
Two-dimensional packing problems using genetic algorithms
Sakait Jain,Hae Chang Gea +1 more
46
TL;DR: In this paper, a new concept of a two-dimensional genetic chromosome is introduced, where the total layout space is divided into a finite number of cells for mapping it into this 2D genetic algorithm chromosome.
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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 2D 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.
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Citations
A Review of the Application ofMeta-Heuristic Algorithms to 2D Strip Packing Problems
E. Hopper,B. C. H. Turton +1 more
TL;DR: The objective of this paper is to present and categorise the solution approaches in the literature for 2D regular and irregular strip packing problems and focus is hereby on the analysis of themethods involving genetic algorithms.
A generic approach for nesting of 2-D parts in 2-D sheets using genetic and heuristic algorithms
A. Ramesh Babu,N. Ramesh Babu +1 more
TL;DR: A new method of representing the sheet and part geometries in discrete form to arrange the parts on the sheet quickly, irrespective of the complexity in the geometry of the sheets and parts is proposed.
118
Solving the two-dimensional irregular objects allocation problems by using a two-stage packing approach
TL;DR: A methodology that hybridizes a two-stage packing approach based on grid approximation with an integer representation based genetic algorithm (GA) is proposed to obtain an efficient allocation of irregular objects in a stock sheet of infinite length and fixed width without overlap.
28
Design for Product Embedded Disassembly
Shingo Takeuchi,Kazuhiro Saitou +1 more
- 01 Jan 2005
TL;DR: In this article, a multi-objective genetic algorithm is used to search for Pareto optimal designs in terms of satisfaction of the distance specification among components, efficient use of locators on compo- nents, profit of EOL scenario, and environmental impact of EO scenario.
24
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58.6K
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Genetic algorithms in search, optimization, and machine learning
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TL;DR: In this article, the authors present the computer techniques, mathematical tools, and research results that will enable both students and practitioners to apply genetic algorithms to problems in many fields, including computer programming and mathematics.