A Simulation Study of Predictable Due-Dates

James K. Weeks
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James K. Weeks: University of North Carolina, Greensboro

Management Science, 1979, vol. 25, issue 4, 363-373

Abstract: This paper describes a simulation study of assigning attainable or predictable due-dates in hypothetical labor and machine constrained job shop settings of varying size and structure. Several predictable due-date assignment rules are developed based on conditional estimates of individual job flow time derived from initial simulation runs. Mean lateness, mean earliness and mean missed due-dates are used as measures of shop performance to compare the various predictable due-date rules under conditions of varying dispatching rules and shop size and structure. Results indicate that due-dates assigned based on expected job flow time and shop congestion information may provide more attainable due-dates than rules based solely upon job characteristics. In addition, better due-date performance appears to be achieved when due-date oriented dispatching rules are employed and when the shop system is not structurally complex.

Keywords: simulation: applications; production/scheduling: job shop; stochastic; inventory/production: simulation (search for similar items in EconPapers)
Date: 1979
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Citations: View citations in EconPapers (23)

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Persistent link: https://EconPapers.repec.org/RePEc:inm:ormnsc:v:25:y:1979:i:4:p:363-373

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