Hybrid Heuristic Algorithms for the Multiobjective Load Balancing of 2D Bin Packing Problems

Impact of decisions in the design process is initially high and declines as the design matures. However, few computational tools are available for the early design phase, thus an opportunity exists to create such tools. New technology opens up new possibilities to create new and novel computational tools. In this work an existing application is adapted for a new novel 3D input device that is named the Leap Motion controller. The controller allows the user to interact with 3D objects on the screen by using fingers and hands. The of result of this work is a conceptual design application which enables very direct manipulation of 3D objects on the screen, which has not before been achieved for this type of application in 3D. An improved human-computer interaction can potentially improve the users understanding of the structural behavior of a model, cognitive engagement in the design task, and encourage further design exploration. Three different cases are implemented which aims to enable the user to explore different design options with emphasis on geometrical form, as this has the greatest potential to improve the structural performance. The case studies demonstrate new potential for building engineering intuition and improving design space exploration through very direct manipulation in 3D.

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Application of Nature Inspired Algorithms to Optimize Multi-objective Two-Dimensional Rectangle Packing Problem

Virk

Singh

2019

J. Ind. Intg. Mgmt.

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This paper considers two-dimensional non-guillotine rectangular bin packing problem with multiple objectives in which small rectangular parts are to be arranged optimally on a large rectangular sheet. The optimization of rectangular parts is attained with respect to three objectives involving maximization of (1) utilization factor, minimization of (2) due dates of rectangles and (3) number of cuts. Three nature based metaheuristic algorithms — Cuckoo Search, Bat Algorithm and Flower Pollination Algorithm — have been used to solve the multi-objective packing problem. The purpose of this work is to consider multiple industrial objectives for improving the overall production process and to explore the potential of the recent metaheuristic techniques. Benchmark test data compare the performance of recent approaches with the popular approaches and also of the different objectives used. Different performance metrics analyze the behavior/performance of the proposed technique. Experimental results obtained in this work prove the effectiveness of the recent metaheuristic techniques used. Also, it was observed that considering multiple and independent factors as objectives for the production process does not degrade the overall performance and they do not necessarily conflict with each other.

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Hybrid Heuristic Algorithms for the Multiobjective Load Balancing of 2D Bin Packing Problems

Cited by 3 publications

References 10 publications

Human-Derived Heuristic Enhancement of an Evolutionary Algorithm for the 2D Bin-Packing Problem

Human-Derived Heuristic Enhancement of an Evolutionary Algorithm for the 2D Bin-Packing Problem

A two-dimensional bin packing-based split-and-pack approach for decomposing large three-dimensional structures into convex items

Application of Nature Inspired Algorithms to Optimize Multi-objective Two-Dimensional Rectangle Packing Problem

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