@article{hodgson_king_thoney_stanislaw_weintraub_zozom_2000, title={On satisfying due-dates in large job shops: idle time insertion}, volume={32}, DOI={10.1080/07408170008963890}, abstractNote={We consider the problem of minimizing maximum lateness in a job shop. A conceptually simple simulation based procedure described in a recent paper by Hodgson et al [1] is modified to provide improved schedules. Computational experimentation is provided to identify the conditions under which the approach is most viable, and to report the procedure's performance on known test problems.}, number={2}, journal={IIE Transactions}, publisher={Informa UK Limited}, author={HODGSON, THOM J. and KING, RUSSELL E. and THONEY, KRISTIN and STANISLAW, NATALIE and WEINTRAUB, ALEXANDER J. and ZOZOM, ANDREW}, year={2000}, month={Feb}, pages={177–180} }
 @article{weintraub_cormier_hodgson_king_wilson_zozom_1999, title={Scheduling with alternatives: a link between process planning and scheduling}, volume={31}, DOI={10.1080/07408179908969910}, abstractNote={The objective of this research is to develop and evaluate effective, computationally efficient procedures for scheduling jobs in a large-scale manufacturing system involving, for example, over 1000 jobs and over 100 machines. The main performance measure is maximum lateness; and a useful lower bound on maximum lateness is derived from a relaxed scheduling problem in which preemption of jobs is based on the latest finish time of each job at each machine. To construct a production schedule that minimizes maximum lateness, an iterative simulation-based scheduling algorithm operates as follows: (a) job queuing times observed at each machine in the previous simulation iteration are used to compute a refined estimate of the effective due date (slack) for each job at each machine; and (b) in the current simulation iteration, jobs are dispatched at each machine in order of increasing slack. Iterations of the scheduling algorithm terminate when the lower bound on maximum lateness is achieved or the iteration limit is reached. This scheduling algorithm is implemented in Virtual Factory, a Windows-based software package. The performance of Virtual Factory is demonstrated in a suite of randomly generated test problems as well as in a large furniture manufacturing facility. To further reduce maximum lateness, a second scheduling algorithm also incorporates a tabu search procedure that identifies process plans with alternative operations and routings for jobs. This enhancement yields improved schedules that minimize manufacturing costs while satisfying job due dates. An extensive experimental performance evaluation indicates that in a broad range of industrial settings, the second scheduling algorithm can rapidly identify optimal or nearly optimal schedules.}, number={11}, journal={IIE Transactions}, author={WEINTRAUB, ALEXANDER and CORMIER, DENIS and HODGSON, THOM and KING, RUSSELL and WILSON, JAMES and ZOZOM, ANDREW}, year={1999}, month={Nov}, pages={1093–1102} }
 @article{hodgson_cormier_weintraub_zozom_1998, title={Note. Satisfying Due Dates in Large Job Shops}, volume={44}, DOI={10.1287/mnsc.44.10.1442}, abstractNote={For the multi-machine job shop scheduling problem, a conceptually simple simulation-based procedure (first proposed by Lawrence and Morton 1986) is shown to be both effective and efficient in providing optimal, or near optimal, schedules for minimizing the maximum lateness, L max . Computational experimentation is used to identify the conditions under which the approach is most viable.}, number={10}, journal={Management Science}, author={Hodgson, Thom J. and Cormier, Denis and Weintraub, Alexander J. and Zozom, Andrew}, year={1998}, month={Oct}, pages={1442–1446} }