Author: Yuchen Li
Publisher: Springer Nature
ISBN: 9811942153
Category : Technology & Engineering
Languages : en
Pages : 164
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Book Description
This book introduces several mathematical models in assembly line balancing based on stochastic programming and develops exact and heuristic methods to solve them. An assembly line system is a manufacturing process in which parts are added in sequence from workstation to workstation until the final assembly is produced. In an assembly line balancing problem, tasks belonging to different product models are allocated to workstations according to their processing times and precedence relationships among tasks. It incorporates two features, uncertain task times, and demand volatility, separately and simultaneously, into the conventional assembly line balancing model. A real-life case study related to the mask production during the COVID-19 pandemic is presented to illustrate the application of the proposed framework and methodology. The book is intended for graduate students who are interested in combinatorial optimizations in manufacturing with uncertain input.
Author: Yuchen Li
Publisher: Springer
ISBN: 9789811942143
Category : Technology & Engineering
Languages : en
Pages : 0
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Book Description
This book introduces several mathematical models in assembly line balancing based on stochastic programming and develops exact and heuristic methods to solve them. An assembly line system is a manufacturing process in which parts are added in sequence from workstation to workstation until the final assembly is produced. In an assembly line balancing problem, tasks belonging to different product models are allocated to workstations according to their processing times and precedence relationships among tasks. It incorporates two features, uncertain task times, and demand volatility, separately and simultaneously, into the conventional assembly line balancing model. A real-life case study related to the mask production during the COVID-19 pandemic is presented to illustrate the application of the proposed framework and methodology. The book is intended for graduate students who are interested in combinatorial optimizations in manufacturing with uncertain input.
Author: Matthias Thürer
Publisher: Springer Nature
ISBN: 3031716299
Category :
Languages : en
Pages : 505
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Book Description
Author: David Bennett
Publisher:
ISBN:
Category : Manufacturing processes
Languages : en
Pages : 384
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Book Description
Author:
Publisher:
ISBN:
Category : Engineering
Languages : en
Pages : 582
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Book Description
Monthly. Papers presented at recent meeting held all over the world by scientific, technical, engineering and medical groups. Sources are meeting programs and abstract publications, as well as questionnaires. Arranged under 17 subject sections, 7 of direct interest to the life scientist. Full programs of meetings listed under sections. Entry gives citation number, paper title, name, mailing address, and any ordering number assigned. Quarterly and annual indexes to subjects, authors, and programs (not available in monthly issues).
Author: Mykel J. Kochenderfer
Publisher: MIT Press
ISBN: 0262331713
Category : Computers
Languages : en
Pages : 350
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Book Description
An introduction to decision making under uncertainty from a computational perspective, covering both theory and applications ranging from speech recognition to airborne collision avoidance. Many important problems involve decision making under uncertainty—that is, choosing actions based on often imperfect observations, with unknown outcomes. Designers of automated decision support systems must take into account the various sources of uncertainty while balancing the multiple objectives of the system. This book provides an introduction to the challenges of decision making under uncertainty from a computational perspective. It presents both the theory behind decision making models and algorithms and a collection of example applications that range from speech recognition to aircraft collision avoidance. Focusing on two methods for designing decision agents, planning and reinforcement learning, the book covers probabilistic models, introducing Bayesian networks as a graphical model that captures probabilistic relationships between variables; utility theory as a framework for understanding optimal decision making under uncertainty; Markov decision processes as a method for modeling sequential problems; model uncertainty; state uncertainty; and cooperative decision making involving multiple interacting agents. A series of applications shows how the theoretical concepts can be applied to systems for attribute-based person search, speech applications, collision avoidance, and unmanned aircraft persistent surveillance. Decision Making Under Uncertainty unifies research from different communities using consistent notation, and is accessible to students and researchers across engineering disciplines who have some prior exposure to probability theory and calculus. It can be used as a text for advanced undergraduate and graduate students in fields including computer science, aerospace and electrical engineering, and management science. It will also be a valuable professional reference for researchers in a variety of disciplines.
Author: Louis Hyman
Publisher: Penguin
ISBN: 0735224099
Category : Business & Economics
Languages : en
Pages : 444
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Book Description
Winner of the William G. Bowen Prize Named a "Triumph" of 2018 by New York Times Book Critics Shortlisted for the 800-CEO-READ Business Book Award The untold history of the surprising origins of the "gig economy"--how deliberate decisions made by consultants and CEOs in the 50s and 60s upended the stability of the workplace and the lives of millions of working men and women in postwar America. Over the last fifty years, job security has cratered as the institutions that insulated us from volatility have been swept aside by a fervent belief in the market. Now every working person in America today asks the same question: how secure is my job? In Temp, Louis Hyman explains how we got to this precarious position and traces the real origins of the gig economy: it was created not by accident, but by choice through a series of deliberate decisions by consultants and CEOs--long before the digital revolution. Uber is not the cause of insecurity and inequality in our country, and neither is the rest of the gig economy. The answer to our growing problems goes deeper than apps, further back than outsourcing and downsizing, and contests the most essential assumptions we have about how our businesses should work. As we make choices about the future, we need to understand our past.
Author: Armin Scholl
Publisher: Physica
ISBN:
Category : Business & Economics
Languages : en
Pages : 344
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Book Description
The book deals with two main decision problems which arise when flow-line production systems are installed and operated. The assembly line balancing problem consists of partitioning the work, necessary to assemble the product(s), among different stations of an assembly line. If several models of a product are jointly processed on a line, this medium-term problem is connected with the short-term problem of determining an operating sequence of the models. In Part I balancing and sequencing problems are discussed, classified, and arranged within a hierarchical planning system. In the present second edition special emphasis is given to u-shaped assembly lines which are important components of modern just-in-time production systems. Part II is concerned with exact and heuristic procedures for solving those decision problems. For each problem type considered, a survey of existing procedures is given and new efficient solution methods are developed. Comprehensive numerical investigations showing the effectiveness of the new methods and their superiority over existing approaches are reported.
Author: Johannes Bisschop
Publisher: Lulu.com
ISBN: 1847539122
Category : Computers
Languages : en
Pages : 318
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Book Description
The AIMMS Optimization Modeling book provides not only an introduction to modeling but also a suite of worked examples. It is aimed at users who are new to modeling and those who have limited modeling experience. Both the basic concepts of optimization modeling and more advanced modeling techniques are discussed. The Optimization Modeling book is AIMMS version independent.
Author: David E. Bell
Publisher: Thomson South-Western
ISBN:
Category : Business & Economics
Languages : en
Pages : 228
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Book Description
These authors draw on nearly 50 years of combined teaching and consulting experience to give readers a straightforward yet systematic approach for making estimates about the likelihood and consequences of future events -- and then using those assessments to arrive at sound decisions. The book's real-world cases, supplemented with expository text and spreadsheets, help readers master such techniques as decision trees and simulation, such concepts as probability, the value of information, and strategic gaming; and such applications as inventory stocking problems, bidding situations, and negotiating.
