Online algorithms for a dual version of bin packing
Discrete Applied Mathematics
Probabilistic analysis of algorithms for dual bin packing problems
Journal of Algorithms
Markov chains, computer proofs, and average-case analysis of best fit bin packing
STOC '93 Proceedings of the twenty-fifth annual ACM symposium on Theory of computing
On the sum-of-squares algorithm for bin packing
STOC '00 Proceedings of the thirty-second annual ACM symposium on Theory of computing
Better approximation algorithms for bin covering
SODA '01 Proceedings of the twelfth annual ACM-SIAM symposium on Discrete algorithms
Introduction to Probability Models, Ninth Edition
Introduction to Probability Models, Ninth Edition
An efficient approximation scheme for the one-dimensional bin-packing problem
SFCS '82 Proceedings of the 23rd Annual Symposium on Foundations of Computer Science
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In this paper, we look at the online bounded-space bin cover problem and show how we can use the language of Markov chains to model and analyze the problem. We will use the insights given by the Markov chains to design an algorithm for the online bounded-space bin cover problem. The algorithm is a heuristic that we create by simplifying the Markov chain. We also show how we can use simple methods to improve the efficiency of the algorithm. Finally, we will analyze our algorithm and compare it to a well known online bin cover algorithm.