[PDF] Models And Solution Methods For Chemical Production Scheduling eBook

Author : Christos T. Maravelias
Publisher : Cambridge University Press
Page : 459 pages
File Size : 45,65 MB
Release : 2021-05-06
Category : Mathematics
ISBN : 1107154758

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Understand common scheduling as well as other advanced operational problems with this valuable reference from a recognized leader in the field. Beginning with basic principles and an overview of linear and mixed-integer programming, this unified treatment introduces the fundamental ideas underpinning most modeling approaches, and will allow you to easily develop your own models. With more than 150 figures, the basic concepts and ideas behind the development of different approaches are clearly illustrated. Addresses a wide range of problems arising in diverse industrial sectors, from oil and gas to fine chemicals, and from commodity chemicals to food manufacturing. A perfect resource for engineering and computer science students, researchers working in the area, and industrial practitioners.

Author :
Publisher :
Page : 0 pages
File Size : 27,68 MB
Release : 2015
Category :
ISBN :

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Optimization-based strategies to solve problems in production scheduling have been extensively used in the last decades due to their generality, flexibility and potential to find the best solutions in terms of costs, customer satisfaction, and efficiency. Traditionally, most efforts have been directed towards the development of mathematical models that are computationally tractable. However, the effective solution of large-scale scheduling models remains nontrivial. The main objective of this thesis is the development of solution methods for the different types of chemical plants. Our discussion is largely motivated by a new approach to the analysis of timing and inventory restrictions in scheduling problems. First, we propose a family of algorithms that are suitable for maximization problems in network environments. By preprocessing the original data we calculate parameters that are used to develop tightening constraints. We also introduce the concept of variable start and finish times and derive expressions to relate them and connect them with original decision variables. By means of computational experiments we show the effectiveness of these methods in improving the solution process of optimization-based models for scheduling. Second, we develop a new family of discrete-time models for sequential environments. Almost all the existing models in the literature use a continuous representation of time. We discuss the advantages of discrete-time models and propose different solution methods to improve their computational performance. A computational study is included to test the improvements and compare with existing approaches. Significant reduction in computational time and optimality gap is achieved. Third, we extend methods based on reformulations and tightening constraints from discrete-time to continuous time models in network environments. We use specific characteristics of the latter to improve computational performance, testing our methods on several benchmark instances. Finally we test the proposed methods on large-scale instances for which optimal solutions had not been found before or whose computational performances demanded long solution times. This way we show that our formulations and methods improve the tractability of industrial-scale instances. Optimal or near-optimal solutions are now accessible in reasonable time for many cases for which only suboptimal solutions from heuristics procedures or empirical methods were available.

Author : Ho Jae Lee
Publisher :
Page : 0 pages
File Size : 15,61 MB
Release : 2019
Category :
ISBN :

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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.

Author :
Publisher :
Page : 264 pages
File Size : 17,36 MB
Release : 2014
Category :
ISBN :

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Chemical production scheduling optimization has the potential to reduce operating cost, increase profits, and improve efficiency. These optimization problems often formulated as mixed integer programming models which, despite advances in computer hardware and optimization software, remain hard to solve. We first formulate a more general model and then develop several solution methods to speed up the computational times. We show that the production environment can be defined by material handling constraints and formulate a general model that is valid for all production environments. We develop new formulations for processes with changeovers and compare their relative tightness and present computational results for several example problems. In the first solution method, customer orders are propagated backwards through the network to find the minimum amount of material each task must process, providing a lower bound on the number of times each task must run. We extend these methods to the general model. This method is most effective for cost minimization and can lead to a 2-3 order-of-magnitude improvement in computational time. The next method reduces the size of the model by using different time grids for each task, unit, material, and utility. We prove that this formulation will have the same optimal solution as a single-grid formulation. This method is most effective for makespan. The third method uses a parallel batch-and-bound algorithm. The scheduling problem is divided into subproblems by branching on the number of times each task runs. Each of these subproblems is solved in parallel by a separate core and may be divided further. Many difficult problems can be solved to optimality with this method. The final method is the simplest and most effective. Many equivalent schedules can be formed by simply shifting tasks in units with idle time earlier or later. These schedules have the same number of batches and similar objectives. Introducing a new integer variable representing the number of batches of each task allows the solver to branch on this variable to find truly different schedules quickly. This method is the most effective with over 2, 3, or 4 orders-of-magnitude improvements for makespan, profit, and cost optimization respectively.

Author : Christos T. Maravelias
Publisher : Cambridge University Press
Page : 460 pages
File Size : 50,12 MB
Release : 2021-05-06
Category : Technology & Engineering
ISBN : 1009038540

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Understand common scheduling as well as other advanced operational problems with this valuable reference from a recognized leader in the field. Beginning with basic principles and an overview of linear and mixed-integer programming, this unified treatment introduces the fundamental ideas underpinning most modeling approaches, and will allow you to easily develop your own models. With more than 150 figures, the basic concepts and ideas behind the development of different approaches are clearly illustrated. Addresses a wide range of problems arising in diverse industrial sectors, from oil and gas to fine chemicals, and from commodity chemicals to food manufacturing. A perfect resource for engineering and computer science students, researchers working in the area, and industrial practitioners.

Author :
Publisher : Elsevier
Page : 3064 pages
File Size : 30,57 MB
Release : 2017-09-21
Category : Technology & Engineering
ISBN : 0444639705

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27th European Symposium on Computer Aided Process Engineering, Volume 40 contains the papers presented at the 27th European Society of Computer-Aided Process Engineering (ESCAPE) event held in Barcelona, October 1-5, 2017. It is a valuable resource for chemical engineers, chemical process engineers, researchers in industry and academia, students, and consultants for chemical industries. Presents findings and discussions from the 27th European Society of Computer-Aided Process Engineering (ESCAPE) event

Author : Anton A. Kiss
Publisher : Elsevier
Page : 1892 pages
File Size : 50,40 MB
Release : 2019-07-03
Category : Computers
ISBN : 0128186356

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The 29th European Symposium on Computer Aided Process Engineering, contains the papers presented at the 29th European Symposium of Computer Aided Process Engineering (ESCAPE) event held in Eindhoven, The Netherlands, from June 16-19, 2019. It is a valuable resource for chemical engineers, chemical process engineers, researchers in industry and academia, students, and consultants for chemical industries. Presents findings and discussions from the 29th European Symposium of Computer Aided Process Engineering (ESCAPE) event

Author : Mariano Martín Martín
Publisher : CRC Press
Page : 786 pages
File Size : 38,85 MB
Release : 2019-06-06
Category : Computers
ISBN : 0429835434

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The field of Chemical Engineering and its link to computer science is in constant evolution and new engineers have a variety of tools at their disposal to tackle their everyday problems. Introduction to Software for Chemical Engineers, Second Edition provides a quick guide to the use of various computer packages for chemical engineering applications. It covers a range of software applications from Excel and general mathematical packages such as MATLAB and MathCAD to process simulators, CHEMCAD and ASPEN, equation-based modeling languages, gProms, optimization software such as GAMS and AIMS, and specialized software like CFD or DEM codes. The different packages are introduced and applied to solve typical problems in fluid mechanics, heat and mass transfer, mass and energy balances, unit operations, reactor engineering, process and equipment design and control. This new edition offers a wider view of packages including open source software such as R, Python and Julia. It also includes complete examples in ASPEN Plus, adds ANSYS Fluent to CFD codes, Lingo to the optimization packages, and discusses Engineering Equation Solver. It offers a global idea of the capabilities of the software used in the chemical engineering field and provides examples for solving real-world problems. Written by leading experts, this book is a must-have reference for chemical engineers looking to grow in their careers through the use of new and improving computer software. Its user-friendly approach to simulation and optimization as well as its example-based presentation of the software, makes it a perfect teaching tool for both undergraduate and master levels.

Author : Peter Kischka
Publisher : Springer Science & Business Media
Page : 414 pages
File Size : 27,7 MB
Release : 2012-12-06
Category : Business & Economics
ISBN : 3642576036

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This title represents an ambitious undertaking, namely a broad view on the nature of intelligent decision making, which is characterized by the use of models and methods in the framework of decision support for management. With this title we want to reflect the scope of our field, but, at the same time, honor our colleague th Paul Stahly on the occasion of his 65 birthday. Paul Stahly has over decades invested his energy in developing the area of Operations Research from such a broad point of view. He has done this not only at his chairs at the HSG / University of St. Gallen and the University of Linz, but also on a broad international level as editor of ITOR and as influential member of all the Operations Research societies in the German speaking countries. He has, in particular, enriched our area by application-oriented research and industrial projects in fields such as logistics, emergency planning, [mance, and others, and he was pivotal in strengthening the cooperation between the national and international OR societies, particular in the German speaking area. VI Consequently, many colleagues who partly cooperated very closely with him, have contributed to this monograph. Some of these contributions have been presented at a colloquium in January 2001 in St. Gallen in honor of Paul Stahly. This colloquium was attended by many colleagues coming from Germany, Austria, Switzerland, Italy and even from the United States.

Author : Egon Balas
Publisher : Springer
Page : 238 pages
File Size : 25,19 MB
Release : 2018-11-27
Category : Mathematics
ISBN : 3030001482

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Disjunctive Programming is a technique and a discipline initiated by the author in the early 1970's, which has become a central tool for solving nonconvex optimization problems like pure or mixed integer programs, through convexification (cutting plane) procedures combined with enumeration. It has played a major role in the revolution in the state of the art of Integer Programming that took place roughly during the period 1990-2010. The main benefit that the reader may acquire from reading this book is a deeper understanding of the theoretical underpinnings and of the applications potential of disjunctive programming, which range from more efficient problem formulation to enhanced modeling capability and improved solution methods for integer and combinatorial optimization. Egon Balas is University Professor and Lord Professor of Operations Research at Carnegie Mellon University's Tepper School of Business.