English [en], .pdf, 🚀/lgli/lgrs/nexusstc/zlib, 5.9MB, 📘 Book (non-fiction), nexusstc/Linear Programming and Resource Allocation Modeling/a3f949499fde580d16503f0efae5cb81.pdf
Linear Programming and Resource Allocation Modeling 🔍
Wiley & Sons, Incorporated, John, 1st edition, Hoboken, NJ, 2018
Michael J. Panik 🔍
description
Guides in the application of linear programming to firm decision making, with the goal of giving decision-makers a better understanding of methods at their disposal Useful as a main resource or as a supplement in an economics or management science course, this comprehensive book addresses the deficiencies of other texts when it comes to covering linear programming theory-especially where data envelopment analysis (DEA) is concerned-and provides the foundation for the development of DEA. Linear Programming and Resource Allocation Modeling begins by introducing primal and dual problems via an optimum product mix problem, and reviews the rudiments of vector and matrix operations. It then goes on to cover: the canonical and standard forms of a linear programming problem; the computational aspects of linear programming; variations of the standard simplex theme; duality theory; single- and multiple- process production functions; sensitivity analysis of the optimal solution; structural changes; and parametric programming. The primal and dual problems are then reformulated and re-examined in the context of Lagrangian saddle points, and a host of duality and complementary slackness theorems are offered. The book also covers primal and dual quadratic programs, the complementary pivot method, primal and dual linear fractional functional programs, and (matrix) game theory solutions via linear programming, and data envelopment analysis (DEA). This book: -Appeals to those wishing to solve linear optimization problems in areas such as economics, business administration and management, agriculture and energy, strategic planning, public decision making, and health care -Fills the need for a linear programming applications component in a management science or economics course -Provides a complete treatment of linear programming as applied to activity selection and usage -Contains many detailed example problems as well as textual and graphical explanations Linear Programming and Resource Allocation Modeling is an excellent resource for professionals looking to solve linear optimization problems, and advanced undergraduate to beginning graduate level management science or economics students. Read more... Abstract: Guides in the application of linear programming to firm decision making, with the goal of giving decision-makers a better understanding of methods at their disposal Useful as a main resource or as a supplement in an economics or management science course, this comprehensive book addresses the deficiencies of other texts when it comes to covering linear programming theory-especially where data envelopment analysis (DEA) is concerned-and provides the foundation for the development of DEA. Linear Programming and Resource Allocation Modeling begins by introducing primal and dual problems via an optimum product mix problem, and reviews the rudiments of vector and matrix operations. It then goes on to cover: the canonical and standard forms of a linear programming problem; the computational aspects of linear programming; variations of the standard simplex theme; duality theory; single- and multiple- process production functions; sensitivity analysis of the optimal solution; structural changes; and parametric programming. The primal and dual problems are then reformulated and re-examined in the context of Lagrangian saddle points, and a host of duality and complementary slackness theorems are offered. The book also covers primal and dual quadratic programs, the complementary pivot method, primal and dual linear fractional functional programs, and (matrix) game theory solutions via linear programming, and data envelopment analysis (DEA). This book: -Appeals to those wishing to solve linear optimization problems in areas such as economics, business administration and management, agriculture and energy, strategic planning, public decision making, and health care -Fills the need for a linear programming applications component in a management science or economics course -Provides a complete treatment of linear programming as applied to activity selection and usage -Contains many detailed example problems as well as textual and graphical explanations Linear Programming and Resource Allocation Modeling is an excellent resource for professionals looking to solve linear optimization problems, and advanced undergraduate to beginning graduate level management science or economics students
Alternative filename
lgrsnf/Panik_Linear Programming and Resource Allocation Modeling.pdf
Alternative filename
lgli/Panik_Linear Programming and Resource Allocation Modeling.pdf
Alternative author
Panik, Michael J.
Alternative publisher
John Wiley & Sons, Incorporated
Alternative publisher
Wiley & Sons, Limited, John
Alternative publisher
American Geophysical Union
Alternative publisher
Wiley Blackwell
Alternative edition
John Wiley & Sons, Inc., Hobokne, NJ, 2019
Alternative edition
United States, United States of America
Alternative edition
Hoboken, NJ, 2019
Alternative edition
Chichester, 2018
metadata comments
0
metadata comments
lg2274500
metadata comments
{"edition":"1","isbns":["1119509440","1119509459","1119509467","1119509475","9781119509448","9781119509455","9781119509462","9781119509479"],"last_page":449,"publisher":"Wiley"}
Alternative description
<p><b>Guides in the application of linear programming to firm decision making, with the goal of giving decision-makers a better understanding of methods at their disposal</b></p> <p>Useful as a main resource or as a supplement in an economics or management science course, this comprehensive book addresses the deficiencies of other texts when it comes to covering linear programming theory--especially where data envelopment analysis (DEA) is concerned--and provides the foundation for the development of DEA.</p> <p><i>Linear Programming and Resource Allocation Modeling</i> begins by introducing primal and dual problems via an optimum product mix problem, and reviews the rudiments of vector and matrix operations. It then goes on to cover: the canonical and standard forms of a linear programming problem; the computational aspects of linear programming; variations of the standard simplex theme; duality theory; single- and multiple- process production functions; sensitivity analysis of the optimal solution; structural changes; and parametric programming. The primal and dual problems are then reformulated and re-examined in the context of Lagrangian saddle points, and a host of duality and complementary slackness theorems are offered. The book also covers primal and dual quadratic programs, the complementary pivot method, primal and dual linear fractional functional programs, and (matrix) game theory solutions via linear programming, and data envelopment analysis (DEA). This book:</p> <ul> <li>Appeals to those wishing to solve linear optimization problems in areas such as economics, business administration and management, agriculture and energy, strategic planning, public decision making, and health care</li> <li>Fills the need for a linear programming applications component in a management science or economics course</li> <li>Provides a complete treatment of linear programming as applied to activity selection and usage</li> <li>Contains many detailed example problems as well as textual and graphical explanations</li> </ul> <p><i>Linear Programming and Resource Allocation Modeling</i> is an excellent resource for professionals looking to solve linear optimization problems, and advanced undergraduate to beginning graduate level management science or economics students.</p>
date open sourced
2018-10-17
🚀 Fast downloads
Become a member to support the long-term preservation of books, papers, and more. To show our gratitude for your support, you get fast downloads. ❤️
- Option #1: Fast Partner Server #1 (recommended) (open in viewer) (no redirect) (short filename) (no browser verification or waitlists)
- Option #2: Fast Partner Server #2 (open in viewer) (no redirect) (short filename)
- Option #3: Fast Partner Server #3 (open in viewer) (no redirect) (short filename)
- Option #4: Fast Partner Server #4 (open in viewer) (no redirect) (short filename)
- Option #5: Fast Partner Server #5 (open in viewer) (no redirect) (short filename)
🐢 Slow downloads
From trusted partners. More information in the FAQ. (might require browser verification — unlimited downloads!)
- Option #1: Slow Partner Server #1 (slightly faster but with waitlist)
- Option #2: Slow Partner Server #2 (slightly faster but with waitlist)
- Option #3: Slow Partner Server #3 (no waitlist, but can be very slow)
- After downloading: Open in our viewer
External downloads
All download options have the same file, and should be safe to use. That said, always be cautious when downloading files from the internet, especially from sites external to Anna’s Archive. For example, be sure to keep your devices updated.
-
For large files, we recommend using a download manager to prevent interruptions.
Recommended download managers: JDownloader -
You will need an ebook or PDF reader to open the file, depending on the file format.
Recommended ebook readers: Anna’s Archive online viewer, ReadEra, and Calibre -
Use online tools to convert between formats.
Recommended conversion tools: CloudConvert -
You can send both PDF and EPUB files to your Kindle or Kobo eReader.
Recommended tools: Amazon‘s “Send to Kindle” and djazz‘s “Send to Kobo/Kindle” -
Support authors and libraries
✍️ If you like this and can afford it, consider buying the original, or supporting the authors directly.
📚 If this is available at your local library, consider borrowing it for free there.
Total downloads:
A “file MD5” is a hash that gets computed from the file contents, and is reasonably unique based on that content. All shadow libraries that we have indexed on here primarily use MD5s to identify files.
A file might appear in multiple shadow libraries. For information about the various datasets that we have compiled, see the Datasets page.
For information about this particular file, check out its JSON file. Live/debug JSON version. Live/debug page.