The principal challenge of inventory control in supply chains is that the interacting autonomous enterprises have to plan their production and logistics under information asymmetry, driven by different, often conflicting objectives. In this paper, four different computational approaches are investigated to cope with this challenge: decomposition, integration, coordination, and bilevel programmi...

The need for dynamic operation in the process industry is described by Backx et al. [1]. The economics are increasingly driven by the market and this requires flexible supply chains. In such an environment it is much harder to optimize economic performance while maintaining the required product quality and honoring operational constraints. Therefore it is expected that the current industrial st...

Learning control is a very effective approach for tracking repetitive processes. In this paper, the stable-inversion based learning controller as presented in (Ghosh, J. and Paden, B., 1999, ‘‘Iterative Learning Control for Nonlinear Nonminimum Phase Plants with Input Disturbances,’’ in Proc. of American Control Conference; Ghosh, J. and Paden, B., 1999, ‘‘A pseudo-inverse based Iterative Learn...

Ghosh et al. [GMM98] presented a novel approach for providing fault tolerance for sets of independent, periodic tasks with rate-monotonic scheduling. We extend this approach to tasks that share logical or physical resources (and hence require synchronization). We show that if the simple rate-monotonic dispatch is replaced by stack scheduling [BakSl], the worst-case blocking overhead of the stac...

Background: Consistent with Rule 100 of Michigan’s Water Quality Standards (WQS), Lake Allegan is protected for warmwater fishery, other indigenous aquatic life and wildlife, agriculture, navigation, industrial water supply, partial body contact recreation, and total body contact recreation. Prioritization of the Lake Allegan TMDL was driven by Michigan’s five-year rotating watershed assessment...

We use non-Gaussian features in U.S. macroeconomic data to identify aggregate supply and demand shocks while imposing minimal economic assumptions. Recessions in the 1970s and 1980s were driven primarily by supply shocks, later recessions were driven primarily by demand shocks, and the Great Recession exhibited large negative shocks to both demand and supply. We estimate “macro risk factors” th...

We present an analytical tool to identify the optimal supply chain design and resource allocation that integrates supply chain planning with information from management accounting. Using costing data based on Time-Driven Activity Based Costing techniques, an optimization model determines the most beneficial route to market (i.e., with the lowest cost-to-serve) given the resource constraints in ...

Firms no longer compete as autonomous entities and prefer to join in a supply chain alliance to take advantage of highly competitive business situation. Supply chain coordination has a great impact on strategic partnering and success of a firm in competitive business environment. In this paper, we propose a system dynamics simulation model for strategic partner selection in supply chain. Our mo...