A genetic algorithm for a 2D industrial packing problem
Computers and Industrial Engineering
Practical Handbook of Genetic Algorithms
Practical Handbook of Genetic Algorithms
Computers and Industrial Engineering
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Evolution of Appropriate Crossover and Mutation Operators in a Genetic Process
Applied Intelligence
Simultaneously Applying Multiple Mutation Operators in Genetic Algorithms
Journal of Heuristics
Efficient parts nesting schemes for improving stereolithography utilization
Computer-Aided Design
SMI 2013: Orthogonal slicing for additive manufacturing
Computers and Graphics
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The performance of a rapid prototyping technology depends, to a great extent, on the way parts are oriented and packed on the machine's build platform. The present work focuses on stereolithography systems. It describes a pre-processing methodology that 'automates' the procedure of finding 'good' fabrication orientations and packing arrangements. The method proposed consists of two separate, but interrelated, stages: the orientation and the packing stage. At first, each part is appropriately oriented to achieve better surface quality and either minimal support structure or lower build time or minimal projection area. The second stage considers the projections of the parts on the fabrication platform. The associated 2D bin-packing problem is addressed by a genetic algorithm in conjunction with a new improved placement rule. The performance of the present approach is demonstrated via two sets of case studies, which concern simple nearly orthogonal-shaped parts and representative 'real-world' objects/parts.