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Recently several authors have concentrated their efforts in developing models to determine the economic lot size for multi‐stage systems. This is due to the fact that an increasing number of organisations are implementing material requirements planning systems. Numerous models have been developed and tested on problems with finite and rolling horizons and with deterministic time varying demand patterns.

This paper examines the impact of forecast window intervals on replanning frequencies for a rolling horizon master production schedule (MPS). The problem environment for this study is an actual MPS operation of a paint company and includes features such as multiple production lines, multiple products, capacity constraints, minimum inventory requirements. A mixed integer goal programming model formulated for the MPS problem is used to analyze the impact of forecast window interval length on replanning frequencies and MPS performance in a rolling horizon setting. Given demand certainty, results indicate that the length of the forecast window interval influences the choice of replanning frequency for this company environment. A three‐month forecast window interval with a two‐month replanning frequency provided the best MPS performance in terms of total cost.

The purpose of this paper is to propose a rolling horizon procedure (RHP) to deal with the large‐scale and strongly NP‐hard problem on cooperative lockage‐timetables and service‐policies of the five locks in the Three Gorges Project.

RHP based approach is composed of a series of periodical short‐time sub‐optimizations instead of global optimization. Each of the sub‐optimizations is modeled by a mixed‐integer‐programming and solved by a branch and bound algorithm with terminal penalty.

The RHP method is found to be effective and efficient. The size of the rolling horizon is positively correlated to the total weighted area of ships.

Precision of short‐time predictions is the main limitation.

This procedure promotes the navigation capacity of the Three Gorges Project and proposes a solution to the lockage‐scheduling problem of the Three Gorges Project.

This study aims to reduce the warping deformation of the stainless composite plate after removal strake by using a finite element method. A three-dimensional thermo-mechanical coupled elastic-plastic finite element model has been suggested by using ABAQUS to simulate the multi-pass hot rolling of stainless composite plate.

A three-dimensional thermo-mechanical coupled elastic-plastic finite element model has been suggested by using ABAQUS to simulate the multi-pass hot rolling of stainless composite plate. Warping deformation rules of 316L/Q345R stainless composite plate after removal strake have been analyzed. Moreover, the influences of some different rolling parameters on this deformation have been discussed.

The warping deformation just varies in the range of cladding ratio from 0.1 to 0.25. Therefore, cladding ratio does not have a great influence on warping deformation.

The results show that higher heating temperature, larger final thickness and less rolling passes are beneficial for reducing the warping deformation.

Previous research has not addressed the problem of developing a master production schedule (MPS) for production systems with minimum batch‐size production restrictions. Proposes a weighted integer goal‐programming model for the development of a rolling horizon master production schedule, under conditions of demand certainty, for a process industry environment with multiple production lines and minimum batch‐size production restrictions. The presence of multiple and often conflicting goals prevalent in production planning and scheduling is explicitly incorporated in the model. The model can easily be implemented on a microcomputer and the master production schedule developed is in spreadsheet format and can easily be understood by a practitioner. Uses a case study conducted for a paint company to illustrate and validate the model. Results show that the MPS developed using the proposed model is superior in terms of total cost when compared with actual company performance.

The purpose of the paper is to show how professional tools trigger workplace learning. The daily mundane work of Swedish police officers has been studied to investigate how the use of police tools triggers learning through discussions in police practice.

Data were collected through a field study consisting of extensive observations and interviews. The interviews mainly took place in the actual practice of the officers. Situated learning and communities of practice served as an analytical lens.

The study revealed how the use of specific police tools resulted in conversations among the officers. Theses conversations are claimed to be vital parts of the community, and thus the learning of the community of police practice. The paper shows how tools make the ways of working, i.e. police practice, available for discussion and collective reflection.

The paper is an in‐depth investigation of a relatively closed sector of society. The paper can inspire researchers to embark on similar studies of other practices. The paper provides novel ways of thinking about how learning takes place in everyday work, not planned and organized by management, but rather as a necessity driven by new tools, and how tools are involved in work.

When sales vary significantly according to season, the manufacturer makes special provisions to integrate the acquisition of raw materials and labour with an effective production schedule which satisfies customers′ requirements. The recommended procedure is called aggregate planning, and many algorithms produce a good definitive solution. However, they have been ignored by industry. The empirical research presented here looks at such planning in a sample of 20 Australian factories. It sheds some light on the acknowledged gap between theory and practice, and suggests that business strategy, the extent of the seasonal distortion, and the tactical remedies available, are all linked. Strategic and tactical considerations tend to bypass the aggregate planning step, and the problem is ultimately resolved at the master production schedule level.

Past research in examining the performance of alternative lot‐sizing rules has focused on the total cost of inventory carrying cost and set‐up cost. Although this cost‐related performance measure is significant for evaluating the overall efficiency of production systems, there are other variations such as frequent rescheduling, generally referred to as system nervousness, occurring that would affect the production scheduling and subsequently the system performance. Expands the performance criteria to re‐evaluate the effectiveness of using several commonly tested lot‐sizing rules in a multi‐level MRP system under stochastic operating environments by means of a simulation study. Results indicate that the Silver‐Meal algorithm seem to perform very well under most operating environments tested. Also, the operating environments play a significant role in the relative performance of lot‐sizing rules tested.

Examines two differing manufacturing operations and characterizes their manufacturing planning and control (MPC) systems. The primary concern of this categorization analysis is to examine the similarities and differences between the flexibilities inherent in each operation′s MPC system. One company has a system which is primarily a push‐based system, the other largely a pull‐based system. Examines different categories of flexibility in terms of both range flexibility (how far the system can cope with the change) and response flexibility (how fast the system can cope with change). The major conclusion is that pull‐based systems have flexibility characteristics which are characterized by relatively clearly thought‐out discontinuities in their range response curves.