On the use of equivalence classes for optimal and sub-optimal bin covering
Paper in proceedings, 2019

Bin covering is an important optimization problem in many industrial fields, such as packaging, recycling, and food processing. The problem concerns a set of items, each with its own value, that are to be collected into bins in such a way that the total value of each bin, as measured by the sum of its item values, is not lower than a target value. The optimization problem concerns maximizing the number of bins. This is a combinatorial NP-hard problem, for which true optimal solutions can only be calculated in specific cases, such as when restricted to a small number of items. To get around this problem, many suboptimal approaches exist. This paper describes a formulation of the bin covering that allows to find the true optimum for a rather large number of items, over 1000. Also presented is a suboptimal solution, which is compared to the true optimum and found to come within less than 10% of the optimum.

Author

Sabino Francesco Roselli

Chalmers, Electrical Engineering, Systems and control, Automation

Fredrik Hagebring

Chalmers, Electrical Engineering, Systems and control, Automation

Sarmad Riazi

Chalmers, Electrical Engineering, Systems and control, Automation

Martin Fabian

Chalmers, Electrical Engineering, Systems and control, Automation

Knut Åkesson

Chalmers, Electrical Engineering, Systems and control, Automation

IEEE International Conference on Automation Science and Engineering

21618070 (ISSN) 21618089 (eISSN)

Vol. 2019-August 1004-1009 8843323

15th IEEE International Conference on Automation Science and Engineering, CASE 2019
Vancouver, Canada,

Engineering Tool Chain for Efficient and Iterative Development of Smart Factories (ENTOC)

VINNOVA, 2016-09-01 -- 2019-08-31.

Areas of Advance

Production

Subject Categories

Computational Mathematics

Control Engineering

Mathematical Analysis

DOI

10.1109/COASE.2019.8843323

More information

Latest update

9/21/2020