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Given the importance of incorporating transportation costs in inventory replenishment and supplier selection decisions, this article addresses the issue of supplier selection and order quantity allocation in a multi-stage serial supply chain system with multiple suppliers considering inventory replenishment, holding, and transportation costs simultaneously. We propose a mixed integer nonlinear programming model to determine the optimal inventory policy for the stages in the supply chain and allocation of orders among the suppliers at the initial stage. Transportation costs between consecutive stages are modeled using a piecewise constant setup cost structure arising from a full truckload freight rate cost model. Vehicles of different capacities are available to transport materials from the suppliers to the manufacturing facility and between the remaining stages of the supply chain. The usefulness of the model is discussed with an example. Sensitivity analysis is carried out to determine the effect of cost parameters on supplier order allocation. The analysis shows that the selection of suppliers and the corresponding order quantities are affected by the variations in supply chain costs parameters. In addition, the advantages of using an integrated approach versus a sequential approach for inventory replenishment and supplier selection decisions are shown. Computational results show that the integrated approach yields average savings of 4.88% in total cost and 15.31% in logistics costs over the sequential approach.

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This paper presents a large-scale document-level comparison of two major bibliographic data sources: Scopus and Dimensions. The focus is on the differences in their coverage of documents at two levels of aggregation: by country and by institution. The main goal is to analyze whether Dimensions offers as good new opportunities for bibliometric analysis at the country and institutional levels as it does at the global level. Differences in the completeness and accuracy of citation links are also studied. The results allow a profile of Dimensions to be drawn in terms of its coverage by country and institution. Dimensions’ coverage is more than 25% greater than Scopus which is consistent with previous studies. However, the main finding of this study is the lack of affiliation data in a large fraction of Dimensions documents. We found that close to half of all documents in Dimensions are not associated with any country of affiliation while the proportion of documents without this data in Scopus is much lower. This situation mainly affects the possibilities that Dimensions can offer as instruments for carrying out bibliometric analyses at the country and institutional level. Both of these aspects are highly pragmatic considerations for information retrieval and the design of policies for the use of scientific databases in research evaluation.

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Given the impact of transportation costs on both supplier selection and inventory replenishment decisions in today's enterprises, this article addresses both problems simultaneously by proposing a mixed integer nonlinear programming model to properly allocate order quantities to the selected set of suppliers while taking into account the purchasing, holding and transportation costs under suppliers' capacity and quality constraints. It is shown that incorporating transportation costs in the process of selecting suppliers and establishing an inventory policy, not only affects the order quantity shipped from selected suppliers, but also the actual selection of suppliers. Because of the difficulty that arises when working with actual transportation freight rates in large-scale problems, two continuous functions that estimate actual freight rates are analyzed. It is shown that the use of these functions is very practical and easy to implement.

A performance-based dynamic scheduling model for random flexible manufacturing systems (FMSs) is presented. The model is built on the mathematical background of supervisory control theory of discrete event systems. The dynamic FMS scheduling is based on the optimization of desired performance measures. A control theory-based system representation is coupled with a goal programming-based multi-criteria dynamic scheduling algorithm. An effectiveness function, representing a performance index, is formulated to enumerate the possible outputs of future schedules. Short-term job scheduling and dispatching decisions are made based on the values obtained by optimizing the effectiveness function. Preventive actions are taken to reduce the difference between actual and desired target values. To analyse the real-time performance of the proposed model, a software environment that included various Visual Basic Application Õ modules, simulation package Arena Õ , and Microsoft Access Õ database was developed. The experimentation was conducted (a) to determine the optimum look-ahead horizons for the proposed model and (b) to compare the model with conventional scheduling decision rules. The results showed that the proposed model outperformed well-known priority rules for most of the common performance measures.