A Mixed Integer Linear Programming (MILP) Scheduling Optimization Approach for Pharmaceutical Manufacturing PDF Download
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Author: Martin Senninger
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Author: Martin Senninger
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Author: Yves Pochet
Publisher: Springer Science & Business Media
ISBN: 0387334777
Category : Business & Economics
Languages : en
Pages : 506
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Book Description
This textbook provides a comprehensive modeling, reformulation and optimization approach for solving production planning and supply chain planning problems, covering topics from a basic introduction to planning systems, mixed integer programming (MIP) models and algorithms through the advanced description of mathematical results in polyhedral combinatorics required to solve these problems. Based on twenty years worth of research in which the authors have played a significant role, the book addresses real life industrial production planning problems (involving complex production structures with multiple production stages) using MIP modeling and reformulation approach. The book provides an introduction to MIP modeling and to planning systems, a unique collection of reformulation results, and an easy to use problem-solving library. This approach is demonstrated through a series of real life case studies, exercises and detailed illustrations. Review by Jakub Marecek (Computer Journal) The emphasis put on mixed integer rounding and mixing sets, heuristics in-built in general purpose integer programming solvers, as well as on decompositions and heuristics using integer programming should be praised... There is no doubt that this volume offers the present best introduction to integer programming formulations of lotsizing problems, encountered in production planning. (2007)
Author: Tadeusz Sawik
Publisher: John Wiley & Sons
ISBN: 1118029100
Category : Technology & Engineering
Languages : en
Pages : 397
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Book Description
A unified, systematic approach to applying mixed integer programming solutions to integrated scheduling in customer-driven supply chains Supply chain management is a rapidly developing field, and the recent improvements in modeling, preprocessing, solution algorithms, and mixed integer programming (MIP) software have made it possible to solve large-scale MIP models of scheduling problems, especially integrated scheduling in supply chains. Featuring a unified and systematic presentation, Scheduling in Supply Chains Using Mixed Integer Programming provides state-of-the-art MIP modeling and solutions approaches, equipping readers with the knowledge and tools to model and solve real-world supply chain scheduling problems in make-to-order manufacturing. Drawing upon the author's own research, the book explores MIP approaches and examples-which are modeled on actual supply chain scheduling problems in high-tech industries-in three comprehensive sections: Short-Term Scheduling in Supply Chains presents various MIP models and provides heuristic algorithms for scheduling flexible flow shops and surface mount technology lines, balancing and scheduling of Flexible Assembly Lines, and loading and scheduling of Flexible Assembly Systems Medium-Term Scheduling in Supply Chains outlines MIP models and MIP-based heuristic algorithms for supplier selection and order allocation, customer order acceptance and due date setting, material supply scheduling, and medium-term scheduling and rescheduling of customer orders in a make-to-order discrete manufacturing environment Coordinated Scheduling in Supply Chains explores coordinated scheduling of manufacturing and supply of parts as well as the assembly of products in supply chains with a single producer and single or multiple suppliers; MIP models for a single- or multiple-objective decision making are also provided Two main decision-making approaches are discussed and compared throughout. The integrated (simultaneous) approach, in which all required decisions are made simultaneously using complex, monolithic MIP models; and the hierarchical (sequential) approach, in which the required decisions are made successively using hierarchies of simpler and smaller-sized MIP models. Throughout the book, the author provides insight on the presented modeling tools using AMPL® modeling language and CPLEX solver. Scheduling in Supply Chains Using Mixed Integer Programming is a comprehensive resource for practitioners and researchers working in supply chain planning, scheduling, and management. The book is also appropriate for graduate- and PhD-level courses on supply chains for students majoring in management science, industrial engineering, operations research, applied mathematics, and computer science.
Author: Charles Sung
Publisher:
ISBN:
Category :
Languages : en
Pages : 232
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Author: Ravendra Singh
Publisher: Elsevier
ISBN: 0444639667
Category : Technology & Engineering
Languages : en
Pages : 700
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Book Description
Process Systems Engineering for Pharmaceutical Manufacturing: From Product Design to Enterprise-Wide Decisions, Volume 41, covers the following process systems engineering methods and tools for the modernization of the pharmaceutical industry: computer-aided pharmaceutical product design and pharmaceutical production processes design/synthesis; modeling and simulation of the pharmaceutical processing unit operation, integrated flowsheets and applications for design, analysis, risk assessment, sensitivity analysis, optimization, design space identification and control system design; optimal operation, control and monitoring of pharmaceutical production processes; enterprise-wide optimization and supply chain management for pharmaceutical manufacturing processes. Currently, pharmaceutical companies are going through a paradigm shift, from traditional manufacturing mode to modernized mode, built on cutting edge technology and computer-aided methods and tools. Such shifts can benefit tremendously from the application of methods and tools of process systems engineering. Introduces Process System Engineering (PSE) methods and tools for discovering, developing and deploying greener, safer, cost-effective and efficient pharmaceutical production processes Includes a wide spectrum of case studies where different PSE tools and methods are used to improve various pharmaceutical production processes with distinct final products Examines the future benefits and challenges for applying PSE methods and tools to pharmaceutical manufacturing
Author: Antonios Fytopoulos
Publisher: Springer Nature
ISBN: 3030909247
Category : Mathematics
Languages : en
Pages : 437
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Book Description
Optimization of Pharmaceutical Processes presents contributions from leading authorities in the fields of optimization and pharmaceutical manufacturing. Formulated within structured frameworks, practical examples and applications are given as guidance to apply optimization techniques to most aspects of pharmaceutical processes from design, to lab and pilot scale, and finally to manufacturing. The increasing demand for better quality, higher yield, more efficient-optimized and green pharmaceutical processes, indicates that optimal conditions for production must be applied to achieve simplicity, lower costs and superior yield. The application of such methods in the pharmaceutical industry is not trivial. Quality of the final product is of major importance to human health and the need for deep knowledge of the process parameters and the optimization of the processes are imperative. The volume, which includes new methods as well as review contributions will benefit a wide readership including engineers in pharmaceuticals, chemical, biological, to name just a few.
Author: Craig W. Schmidt
Publisher:
ISBN:
Category : Integer programming
Languages : en
Pages : 6
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Abstract: "This paper presents a new, real-world scheduling problem concerning the New Product Development process of an agricultural chemical or pharmaceutical company. A Research and Development (R & D) department must schedule the tasks needed to bring a new product to market, in the face of uncertainty about the costs and durations of the tasks, and in the income resulting from introducing the new product. There is a risk that a product will fail a mandatory task, such as an environmental or safety test, and never reach the market. The objective of the schedule is to maximize the expected Net Present Value of the research. A model of this problem initially has a nonlinear, nonconcave objective. The objective is convexified and linearized by appropriate transformations, giving a Mixed Integer Linear Program (MILP). The model uses a continuous time representation and discrete distributions for the stochastic parameters. Different representations of the disjunctive scheduling constraints are discussed. A small numerical example is presented, followed by some conclusions."
Author: Yves Pochet
Publisher: Springer
ISBN: 9780387510569
Category : Business & Economics
Languages : en
Pages : 0
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Book Description
This textbook provides a comprehensive modeling, reformulation and optimization approach for solving production planning and supply chain planning problems, covering topics from a basic introduction to planning systems, mixed integer programming (MIP) models and algorithms through the advanced description of mathematical results in polyhedral combinatorics required to solve these problems. Based on twenty years worth of research in which the authors have played a significant role, the book addresses real life industrial production planning problems (involving complex production structures with multiple production stages) using MIP modeling and reformulation approach. The book provides an introduction to MIP modeling and to planning systems, a unique collection of reformulation results, and an easy to use problem-solving library. This approach is demonstrated through a series of real life case studies, exercises and detailed illustrations. Review by Jakub Marecek (Computer Journal) The emphasis put on mixed integer rounding and mixing sets, heuristics in-built in general purpose integer programming solvers, as well as on decompositions and heuristics using integer programming should be praised... There is no doubt that this volume offers the present best introduction to integer programming formulations of lotsizing problems, encountered in production planning. (2007)
Author: Akhilesh Soni (Ph.D.)
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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Book Description
The thesis consists of research in mixed integer linear programming with applications to scheduling and matrix completion. We first study the problem of scheduling drilling and fracturing of pads in the development of an unconventional oil field. We propose a novel MILP formulation for solving this scheduling problem which considers capacity, operational, precedence, and interference constraints. We also propose a formulation that uses more decision variables, but which provides a stronger linear programming relaxation. Due to the large problem size, solving the full MILP model for instances with many pads and a large number of time periods is intractable. Thus, we also derive a MILP-based rolling horizon framework that solves a sequence of limited horizon, coarser-scale MILP instances in a rolling forward fashion to obtain a solution to the full horizon problem on the daily time scale. We benchmark this approach against a baseline scheduling algorithm that approximates current practice of scheduling pads in the order of discounted production profit with limited lookahead. Our results show that our proposed MILP-based rolling horizon approach can improve the net present value of a field by 4-6%. Next, we present new integer programming approaches to matrix completion problems, both in the real field and in the finite field GF(2). First, we study an integer programming approach for subspace clustering with missing data problem in real field with an assumption that underlying data comes from a union of subspaces. Subspace clustering with missing data is the task of identifying clusters of vectors belonging to the same subspace in a partially observed data matrix whose columns are assumed to lie in a union of K subspaces. We propose a novel mixed-integer linear programming solution framework (MISS-DSG) for this problem that is based on dynamically determining a set of candidate subspaces and optimally assigning data points to the closest selected subspace. MISS-DSG handles a large number of candidate subspaces through its use of Benders decomposition and dynamically generates new candidate subspaces through its use of column generation. We cast the subspace generation problem as a nonlinear, nonconvex optimization problem and propose a gradient-based approximate solution approach. The model has the advantage of integrating the subspace generation and clustering in a single, unified optimization framework without requiring any hyperparameter tuning when number of subspaces and subspaces dimensions are known. Our computational results reveal that the proposed method can achieve higher clustering accuracy than state-of-the-art methods when data is of high-rank, the percentage of missing data is high, or subspaces are close to each other. We next discuss binary matrix completion methods in GF(2) where the arithmetic is done with respect to modulo-2 operations. We give integer linear programming formulations for matrix factorization and completion in GF(2). We first derive formulations making use of McCormick envelopes for the product of two binary variables: a base formulation using a general integer variable and an extended formulation using ideas from disjunctive programming and parity polytopes. The latter formulation characterizes the convex hull of the dot product of two vectors in an extended space. We then derive a novel formulation based on a new class of valid inequalities that also characterizes the convex hull of the dot product in the original space of variables. Our computational results reveal that the proposed formulation results in smaller branch-and-bound trees. Furthermore, we also derive additional classes of valid inequalities linking dot products between two matrix elements.
Author: Thokozani Majozi
Publisher: CRC Press
ISBN: 1482252422
Category : Science
Languages : en
Pages : 450
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Book Description
The manner in which time is captured forms the foundation for synthesis, design, and optimization in batch chemical plants. However, there are still serious challenges with handling time in batch plants. Most techniques tend to assume either a fixed time dimension or adopt time average models to tame the time dimension, thereby simplifying the resu
