The most important models and results of the manufacturing flow line literature are described. These include the major classes of models (asynchronous, synchronous, and continuous); the major features (blocking, processing times, failures and repairs); the major properties (conservation of flow, flow rate-idle time, reversibility, and others); and the relationships among different models. Exact and approximate methods for obtaining quantitative measures of performance are also reviewed. The exact methods are appropriate for small systems. The approximate methods, which are the only means available for large systems, are generally based on decomposition, and make use of the exact methods for small systems. Extensions are briefly discussed. Directions for future research are suggested.

Research on sustainability performance has considerably enriched operations management literature in recent years. However, work with quantitative models is still scarce. This paper thus contributes to revisit classical inventory models by taking sustainability concerns into account. We believe that reducing all aspects of sustainable development to a single objective is not desirable. We thus reformulate the classical economic order quantity model as a multiobjective problem. We propose to refer to this model as the sustainable order quantity model. Then, a multi-echelon extension of the sustainable order quantity model is studied. For both models, the set of efficient solutions (Pareto optimal solutions) is analytically characterized. These results are used to provide some insights about the effectiveness of different regulatory policies to control carbon emissions. We also propose an interactive procedure that allows the decision maker to quickly identify his / her best option among these solutions. The proposed interactive procedure is a new combination of multi-criteria decision analysis techniques.

We consider a capacitated supply system that produces a single item that is demanded by several classes of customers. Each customer class may have a different backorder cost, so stock allocation arises as a key decision problem. We model the supply system as a multi customer make-to-stock queue. Using dynamic programming, we show that the optimal allocation policy has a simple and intuitive structure. In addition, we present an efficient algorithm to compute the parameters of this optimal allocation policy. Finally, for a typical supply chain design problem, we illustrate that ignoring the stock allocation dimension---a frequently encountered simplifying assumption---can lead to incorrect managerial decisions.Inventory/Production, Stock Allocation, Stochastic: Multi-Class, Queues: Make-to-Stock System

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International audienceIn this paper, we analyze a call center with impatient customers. We study how informing customers about their anticipated delays affects performance. Customers react by balking upon hearing the delay announcement and may subsequently renege, particularly if the realized waiting time exceeds the delay that has originally been announced to them. The balking and reneging from such a system are a function of the delay announcement. Modeling the call center as an M/M/s + M queue with endogenized customer reactions to announcements, we analytically characterize performance measures for this model. The analysis allows us to explore the role announcing different percentiles of the waiting time distribution, i.e., announcement coverage, plays on subsequent performance in terms of balking and reneging. Through a numerical study, we explore when informing customers about delays is beneficial and what the optimal coverage should be in these announcements. We show how managers of a call center with delay announcements can control the trade-off between balking and reneging through their choice of announcements to be made

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We consider the problem of dynamically allocating production capacity between two products to minimize the average inventory and backorder costs per unit time in a make-to-stock single machine system. Using sample path comparisons and dynamic programming, we give a characterization of the optimal hedging point policy for a certain region of the state space. The characterization is simple enough to lead to easily implementable heuristics and provides a formal justification of some of the earlier heuristics proposed.