Evaluation of Feedback among Multiple Scheduler Profiles in Fuzzy Genetic Scheduling

This paper extends the earlier studies conducted on multiple scheduler profile in fuzzy genetic scheduling. Multiple schedulers can set up individual fuzzy membership bounds which results in different evaluation of multi-objective problem of single machine scheduling. A new software application enables feedback among schedulers by applying seeding of individual scheduler\u27s population by best chromosomes from other scheduler\u27s population. Few experiments are performed on the aforementioned software application to evaluate the performance of the multi objective single machine scheduling problem by varying the level and frequency of feedback. More improvement is observed as the frequency of the feedback is increased but no significant improvement is observed when the level is increased

Multi-Period Cell Loading and Job Sequencing in a Cellular Manufacturing System

In this paper, a multi-period cell loading problem is addressed, where the objectives are to minimise the number of tardy jobs (nT) in a multi-period planning horizon and optimise the scheduling of tardy jobs. Three cell loading and job scheduling strategies are proposed and tested with two newly developed mixed integer programming models. Additionally, three types of due dates (tight, medium and loose) and three different demand levels were considered. Finally, two tardy job assignment methods were proposed to observe the impact on nT. Case problems were solved based on minimising nT, Tmax and total tardiness (TT) objectives and cost sensitivity analysis was performed. Results indicated that, the first strategy, (early start allowance and tardy job assignment after each period) performed better in terms of nT. For the secondary objectives, tradeoffs were observed among different strategies depending on the type of due date, demand level and tardy job assignment method

Group Scheduling in a Cellular Manufacturing Shop to Minimise Total Tardiness and nT: a Comparative Genetic Algorithm and Mathematical Modelling Approach

In this paper, family and job scheduling in a cellular manufacturing shop is addressed where jobs have individual due dates. The objectives are to minimise total tardiness and the number of tardy jobs. Family splitting among cells is allowed but job splitting is not. Two optimisation methods are employed in order to solve this problem, namely mathematical modelling (MM) and genetic algorithm (GA). The results showed that GA found the optimal solution for most of the problems with high frequency. Furthermore, the proposed GA is efficient compared to the MM especially for larger problems in terms of execution times. Other critical aspects of the problem such as family preemption only, impact of family splitting on common due date scenarios and dual objective scenarios are also solved. In short, the proposed comparative approach provides critical insights for the group scheduling problem in a cellular manufacturing shop with distinctive cases

Evaluation of Feedback among Multiple Scheduler Profiles in Fuzzy Genetic Scheduling

AbstractThis paper extends the earlier studies conducted on multiple scheduler profile in fuzzy genetic scheduling. Multiple schedulers can set up individual fuzzy membership bounds which results in different evaluation of multi-objective problem of single machine scheduling. A new software application enables feedback among schedulers by applying seeding of individual scheduler's population by best chromosomes from other scheduler's population. Few experiments are performed on the aforementioned software application to evaluate the performance of the multi objective single machine scheduling problem by varying the level and frequency of feedback. More improvement is observed as the frequency of the feedback is increased but no significant improvement is observed when the level is increased