Lehigh University

About: Lehigh University is a education organization based out in Bethlehem, Pennsylvania, United States. It is known for research contribution in the topics: Catalysis & Fracture mechanics. The organization has 12684 authors who have published 26550 publications receiving 770061 citations.

Robustness measures and robust scheduling for job shops

Abstract: A robust schedule is defined as a schedule that is insensitive to unforeseen shop floor disturbances given an assumed control policy. In this paper, a definition of schedule robustness is developed which comprises two components: post-disturbance make-span and post-disturbance makespan variability. We have developed robustness measures and robust scheduling methods for the case where a “right-shift” control policy is used. On occurrence of a disruption, the right-shift policy maintains the scheduling sequence while delaying the unfinished jobs as much as necessary to accommodate the disruption. An exact measure of schedule robustness is derived for the case in which only a single disruption occurs within the planning horizon. A surrogate measure is developed for the more complex case in which multiple disruptions may occur. This surrogate measure is then embedded in a genetic algorithm to generate robust schedules for job-shops. Experimental results show that robust schedules significantly outper...

Reliable logistics networks design with facility disruptions

Abstract: This paper studies a strategic supply chain management problem to design reliable networks that perform as well as possible under normal conditions, while also performing relatively well when disruptions strike. We present a mixed-integer programming model whose objective is to minimize the nominal cost (the cost when no disruptions occur) while reducing the disruption risk using the p -robustness criterion (which bounds the cost in disruption scenarios). We propose a hybrid metaheuristic algorithm that is based on genetic algorithms, local improvement, and the shortest augmenting path method. Numerical tests show that the heuristic greatly outperforms CPLEX in terms of solution speed, while still delivering excellent solution quality. We demonstrate the tradeoff between the nominal cost and system reliability, showing that substantial improvements in reliability are often possible with minimal increases in cost. We also show that our model produces solutions that are less conservative than those generated by common robustness measures.

Unravelling structure sensitivity in CO 2 hydrogenation over nickel

Abstract: Continuous efforts in the field of materials science have allowed us to generate smaller and smaller metal nanoparticles, creating new opportunities to understand catalytic properties that depend on the metal particle size. Structure sensitivity is the phenomenon where not all surface atoms in a supported metal catalyst have the same activity. Understanding structure sensitivity can assist in the rational design of catalysts, allowing control over mechanisms, activity and selectivity, and thus even the viability of a catalytic reaction. Here, using a unique set of well-defined silica-supported Ni nanoclusters (1–7 nm) and advanced characterization methods, we prove how structure sensitivity influences the mechanism of catalytic CO2 reduction, the nature of which has been long debated. These findings bring fundamental new understanding of CO2 hydrogenation over Ni and allow us to control both activity and selectivity, which can be a means for CO2 emission abatement through its valorization as a low- or even negative-cost feedstock on a low-cost transition-metal catalyst.