Efficient heuristic algorithms for the weighted set covering problem

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Abstract

In this paper two heuristic algorithms are presented for the weighted set covering problem. The first algorithm uses a simple, polynomial procedure to construct feasible covering solutions. The procedure is shown to possess a worst case performance bound that is a function of the size of the problem. The second algorithm is a solution improvement procedure that attempts to form reduced cost composite solutions from available feasible covering solutions. Computational results are presented for both algorithms on several large set covering problems generated from airline crew scheduling data.

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Edward Baker is an Assistant Professor of Management Science in the School of Business Administration at the University of Miami. He received B.E.S and M.S. degrees from Johns Hopkins University and a DBA from the University of Maryland. His research interests include integer programming, networks, and applications of operations research to problems in transportation and finance.

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