Author : Ho Jae Lee
Release : 2019
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Kind : eBook
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Book Synopsis Mixed-integer Programming Models and Solution Methods for Chemical Production Scheduling by : Ho Jae Lee

Download or read book Mixed-integer Programming Models and Solution Methods for Chemical Production Scheduling written by Ho Jae Lee. This book was released on 2019. Available in PDF, EPUB and Kindle. Book excerpt: Optimization-based chemical production scheduling allows for efficient utilization of available assets and brings significant operational benefits including reduction in costs. Unfortunately, application of such techniques to industrial settings is challenging due to multiple reasons: (i) the optimization models need to be general to accommodate different production processes, (ii) the solution of such models need to be quick to allow for frequent updates to the schedules, and (iii) the models should be capable of providing multiple alternative schedules for the practitioners to compare and implement. The goal of this work is to address the aforementioned challenges and bring optimization-based scheduling techniques closer to industrial applications. First, we develop mathematical programming models for simultaneous batching and scheduling in general sequential production environment while taking into account various process features including storage policies and limited shared utilities. The models are based on novel modeling approaches which allow for exploitation of instance characteristics, thus leading to solution of large-scale instances. Second, we develop a novel framework for a solution algorithm that harnesses the advantages of discrete- and continuous-time scheduling models. Specifically, we propose an algorithm that has modeling flexibility and computational efficiency of discrete-time models, as well as high solution accuracy of their continuous counterparts. We investigate in detail how the algorithm can be improved and extended to solve real-world industrial instances that are thought to be computationally near impossible if transitional methods were to be used. Finally, we develop systematic methods to generate multiple alternative schedules, specifically to account for modeling simplifications introduced in the scheduling models and plant nervousness when revising schedules. We generate alternative schedules by quantifying specific characteristics of a schedule using explicitly defined metrics, which are favored at different degrees by penalizing them in the objective function with varying penalty weights. We show that, by leveraging penalty weights, schedules with desirable properties can be readily found.