A morphing procedure to supplement a simulated annealing heuristic for cost‐ andcoverage‐correlated set‐covering problems

We report on the use of a morphing procedure in a simulated annealing (SA) heuristicdeveloped for set‐covering problems (SCPs). Morphing enables the replacement of columnsin solution with similar but more effective columns (morphs). We developed this procedureto solve minimum cardinality set‐covering problems (MCSCPs) containing columns whichexhibit high degrees of coverage correlation, and weighted set‐covering problems (WSCPs)that exhibit high degrees of both cost correlation and coverage correlation. Such correlationstructures are contained in a wide variety of real‐world problems including many scheduling,design, and location applications. In a large computational study, we found that the morphingprocedure does not degrade the performance of an SA heuristic for SCPs with low degreesof cost and coverage correlation (given a reasonable amount of computation time), and thatit improves the performance of an SA heuristic for problems with high degrees of suchcorrelations.

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