Rolling Time Horizon Research Articles

Workshop scheduling using practical (inaccurate) data Part 2: An investigation of the robustness of scheduling rules in a dynamic and stochastic environment

In research on generating a predictive schedule, the scheduling problem is often viewed as a deterministic problem. However, the real-life job shop environment is stochastic in that information on job attributes and shop floor status is not precisely known in advance. In this situation, in order to increase the effectiveness of a predictive schedule in practice, the focus should be on creating a robust schedule. The purpose of this paper is to investigate the robustness of a number of scheduling rules in a dynamic and stochastic environment using the rolling time horizon approach. A cost-based performance measure is used to evaluate the scheduling rules. The simulation results, under various conditions in a balanced and unbalanced shop, are presented and the effects of the rescheduling interval and operational factors including shop load conditions and a bottleneck on the robustness of the schedule are studied. From the results the key factors that influence the robustness of a scheduling system are identified and, consequently, general guidelines for creating robust schedules are proposed.

Workshop scheduling using practical (inaccurate) data Part 1: The performance of heuristic scheduling rules in a dynamic job shop environment using a rolling time horizon approach

This paper is a report on a simulation study to investigate the performance of a number of scheduling rules on the basis of a rolling time horizon approach for a dynamic job shop environment. The performance measure considered is an economic objective which includes the main costs involved in a scheduling decision. The first purpose of the study was to find the best scheduling rule and the second to investigate the effects of the rescheduling interval on performance and examine whether there is a policy that can always improve performance. The simulation study, which is part of a larger project on practical workshop scheduling, has been carried out under widely varying conditions in terms of due date tightness, shop load level, and shop load balance level. The results show that a recently developed scheduling rule, SPT-C/R, is the most appropriate scheduling rule in minimizing overall cost and that the relationship between performance and rescheduling interval can be shown.

Multilevel lot-sizing heuristics and freezing the master production schedule in material requirements planning systems

This paper compares the performance of a new improved heuristic (STIL) proposed by Coleman and McKnew (1991, Decision Sciences , 22 , 136-156) Wagner-Whitin (WW), cost-modified (MWW) and some simple lot-sizing rules found to perform well by Zhao et al . (1995, International Journal of Production Research , 33 (8), 2241-2276). It also investigates the impact of the lot-sizing ruleson the selection ofthe parametersfor freezing the master production schedule (MPS). The experimental settings include forecasting, master production scheduling and material requirements planning under a rolling time horizon. The result of the study shows that the STIL heuristic, WW rule and MWW rule do not really outperform the simple costmodified Silver-Meal (MSM) and the Silver-Meal/Lot-forLot (SM/LFL), even though they require substantially higher comheuristics against those of the Wagner-Whitin putation time. The study also shows that the selection of the parameters for freezing the MPS is not significantly influenced by the selection of the lot-sizing rules.

Lot-sizing rules and freezing the master production schedule in material requirements planning systems

Freezing the master production schedule (MPS) is one of the frequently used methods for reducing schedule instability in multilevel material requirements planning (MRP) systems. The selection of lot sizing rule and the selection of MPS freezing parameters have been shown to significantly influence MRP performance. This study examines the impact of lot-sizing rule selection on the selection of MPS freezing parameters under rolling time horizons under deterministic demand. A model is built to simulate the Master Production Scheduling and Material Requirements Planning operations in a make-to-order environment. The results show that the selection of lot-sizing rules significantly influences the selection of MPS freezing parameters.

Dispatching, routing, and scheduling of two automated guided vehicles in a flexible manufacturing system

This article presents a new approach for planning the dispatching, conflict-free routing, and scheduling of automated guided vehicles in a flexible manufacturing system. The problem is solved optimally in an integrated manner, contrary to the traditional approach in which the problem is decomposed in three steps that are solved sequentially. The algorithm is based on dynamic programming and is solved on a rolling time horizon. Three dominance criteria are used to limit the size of the state space. The method finds the transportation plan minimizing the makespan (the completion time for all the tasks). Various results are discussed. A heuristic version of the algorithm is also proposed for an extension of the method to many vehicles.

An Interactive Optimization Technique for Short Term Scheduling of Batch Multipurpose Plants

In this paper is discussed a reactive approach for the scheduling of multipurpose chemical batch plants based on the utilization of a rolling time horizon and a lookahead procedure. It is supposed that a previous planning activity has determined product batches to be processed and its due dates in order to maximize the total value added in terms of products deliveries amounts. The proposed short term scheduling technique is started when perturbations in the plant occur and cannot be absorbed in the previous scheduling. The proposed technique is based on a MILP formulation of the State Task Network Representation.

Lot-sizing rules and freezing the master production schedule in material requirements planning systems under demand uncertainty

Freezing the master production schedule (MPS) is one of the frequently used methods for reducing schedule instability in multilevel material requirements planning (MRP) systems. The selection of the lot-sizing rule is an important decision in MRP systems and has been shown to significantly influence MRP performance. This study examines the interaction between the selection of lot-sizing rules and the selection of MPS freezing parameters under rolling time horizons under different demand uncertainty conditions. The findings of this study enhance the understanding of multilevel MRP performance in a more realistic environment and help MRP practitioners select the proper lot-sizing rule and MPS freezing parameters.