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dc.contributor.authorLeighton, Tomen_US
dc.contributor.authorShor, Peteren_US
dc.date.accessioned2023-03-29T14:27:45Z
dc.date.available2023-03-29T14:27:45Z
dc.date.issued1986-05
dc.identifier.urihttps://hdl.handle.net/1721.1/149107
dc.description.abstractThe minimax grid matching problem is a fundamental combinatorial problem associated with the average case analysis of algorithms. The problem has arisen in a number of interesting and seemingly unrelated areas, including wafer-scale integration of systolic arrays, two-dimentsional discrepancy problems, and testing pseudorandom number generators. However, the minimax grid matching problem is best known for its application to the maximum up-right matching problem. The maximum up-right matching problem was originally defined by Karp, Luby and Marchetti-Spaccamela in association with algorithms for 2-dimensional bin packing. More recently, the up-right matching problem has arisen in the average case analysis of on-line algorithms for 1-dimensional bin packing and dynamic allocation. In this paper, we solve both the minimax grid matching problem and the maximum up-right matching problem. As a direct result, we obtain tight upper bounds on the average case behavior of the best algorithms known for 2-dimensional bin packing, 1-dimensional on-line packing and on-line dynamic allocation. The results also solve a long-open question in mathematical statistics.en_US
dc.relation.ispartofseriesMIT-LCS-TM-298
dc.titleTight Bounds for Minimax Grid Matching, with Applications to the Average Case Analysis of Algorithmsen_US


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