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Full-Text Articles in Operations Research, Systems Engineering and Industrial Engineering
Developing An Automated Forecasting Framework For Predicting Operation Room Block Time, Azad Sadr Haghighi
Developing An Automated Forecasting Framework For Predicting Operation Room Block Time, Azad Sadr Haghighi
Wayne State University Theses
Operating rooms are the most important part of the hospitals, since they have highest influence on financial state of the hospital. Because of high uncertainty in surgery cases demands and their durations, the scheduling of the surgeries becomes a very challenging and critical issue in hospitals. One of the most common approaches to overcome this uncertainty is applying block times which is the time intervals allocated to surgery groups in the hospital. Assigning sufficient amount of the time to each block, is very important, since overestimating lead to wasting resources and on the other hand underestimation causes the overtime staffing …
A Customer Choice Modeling Framework For Assortment Planning Of Configurable Products In Automotive Industry, Farah Dubaisi
A Customer Choice Modeling Framework For Assortment Planning Of Configurable Products In Automotive Industry, Farah Dubaisi
Wayne State University Theses
Due to the increased competition in the auto industry, proliferation of the vehicle models and increased customer need for choice and customization, it has become more critical than ever to offer a variety of features and customization flexibility while at the same time restraining and, even better, cutting down the costs. Product complexity, in the automotive industry, can be measured by the size of the assortment offered, i.e., set of vehicle configurations a customer can choose from (e.g., for a given model of a brand). While complexity fosters growth with increased alignment of product characteristics and customer needs, it results …
Self Learning Strategies For Experimental Design And Response Surface Optimization, Adel Alaeddini
Self Learning Strategies For Experimental Design And Response Surface Optimization, Adel Alaeddini
Wayne State University Dissertations
Most preset RSM designs offer ease of implementation and good performance over a wide range of process and design optimization applications. These designs often lack the ability to adapt the design based on the characteristics of application and experimental space so as to reduce the number of experiments necessary. Hence, they are not cost effective for applications where the cost of experimentation is high or when the experimentation resources are limited. In this dissertation, we present a number of self-learning strategies for optimization of different types of response surfaces for industrial experiments with noise, high experimentation cost, and requiring high …