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Implementation of next fit, first fit, best fit, first fit decreasing, and best fit decreasing bin packing algorithms followed by time and space complexity analysis.

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connormcmanigal/bin-packing-analysis

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DATA260P Project 2: Bin Packing Algorithms

View the notebook here: https://connormcmanigal.github.io/bin-packing-analysis/report.pdf

Connor McManigal and Aaron Mui

  • Implemented next fit, first fit, best fit, first fit decreasing, and best fit decreasing
  • Created two custom bin packing algorithms using different packing strategies to improve upon next fit, first fit, and best fit
  • Tested algorithms on 5 unique initializations of radom generated data from sizes 100, 200, 400, 800, 1600, 3200, 6400, 12800, and 25600
  • Measured waste by comparing optimal number of bins(sum of contents/bin size) with number of bins used
  • Took runtime measurements to later approximate implementation based Big-O's
  • Graphed waste and runtime performances on log-log scale to determine the estimated functions of waste and runtime
  • Used statsmodels and OLS to gather estimated coefficients for waste and runtime
  • Provided detailed write up(project2_report.pdf) illustrating our work, plots, and results

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Implementation of next fit, first fit, best fit, first fit decreasing, and best fit decreasing bin packing algorithms followed by time and space complexity analysis.

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