총 준비시간과 처리시간에 따른 학습효과를 고려한 단일설비 일정계획

Abstract

This paper considers the single machine scheduling problems with learning effect on either the setup or processing times, where the setup or processing times decrease according to increasing both the total amount of setups and processing already. Our objective is to find the optimal schedules which minimize makespan, mean flow time, or total absolute differences in completion times (TADC) of the jobs. We characterize the optimal schedules for each scheduling measure and show the optimal scheduling rules to solve the problems with 0(n log n) time. Furthermore, we show that the problems for minimization a weighted sum of makespan and mean flow time are also solved in polynomial-time complexity. The optimal schedules for the bi-criteria are useful for the various environments by fitting the weight of each criterion, makespan and mean flow time, on the aim of the scheduling in the environments.