{"type":"ScholarlyArticle","title":"Expected Solution Quality","authors":[{"name":"John L. Bresina","slug":"john-l-bresina","given":"John L.","family":"Bresina","affiliation":""},{"name":"Mark Drummond","slug":"mark-drummond","given":"Mark","family":"Drummond","affiliation":""},{"name":"Keith Swanson","slug":"keith-swanson","given":"Keith","family":"Swanson","affiliation":""}],"abstract":"This paper presents th e Expected Solution Quality (ESQ) method for statistically characterizing scheduling problems and the performance of schedulers. The ESQ method is demonstrated by applying it to a practical telescope scheduling problem . The method addresses the important and difficult issue of how to meaningfully evaluate the performance of a scheduler on a constrained optimization problem for which an optimal solution is not known. At the heart of ESQ is a Monte Carlo algorithm that estimates a problem's probability density function with respect to solution quality. This \"quality density function\" provides a useful characterization of a scheduling problem, and it also provides a background against which scheduler performance can be meaningfully evaluated . ESQ provides a unitless measure that combines both schedule quality and the amount of time to generate a schedule.","doi":null,"url":"https://ijcai.org/proceedings/1995/204","pdf":"https://ijcai.org/proceedings/1995/0204.pdf","markdown":"https://ijcai.org/proceedings/1995/204.md","bibtex":"https://ijcai.org/proceedings/1995/bibtex/204","volume":{"slug":"1995","title":"Proceedings of the Fourteenth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 1995","url":"https://ijcai.org/proceedings/1995/","year":1995,"location":"Montréal, Québec, Canada","dates":"","editors":"Chris S. Mellish","isbn":"","publisher":"International Joint Conferences on Artificial Intelligence","doi_prefix":""},"section":"Planning","track":"Planning","number":204,"pages":{"first":1583,"last":1590},"keywords":[],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}