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教材-AMPL（pdf版）.pdf

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    01-title
    02-contents
    03-intro
    04-tut1
    05-tut2
    06-tut3
    07-tut4
    08-sets1
    09-sets2
    10-params
    11-linprog
    12-data
    13-tables
    14-command
    15-display
    16-script
    17-solvers
    18-network
    19-colwise
    20-piecewise
    21-nonlinear
    22-complement
    23-integer
    24-refman
    25-index
    AMPL A Modeling Language for Mathematical Programming Second Edition
    AMPL A Modeling Language for Mathematical Programming Second Edition Robert Fourer Northwestern University David M. Gay AMPL Optimization LLC Brian W. Kernighan Princeton University DUXBURY ———————————————— THOMSON ________________________________________________________________________________ Australia • Canada • Mexico • Singapore • Spain • United Kingdom • United States
    This book was typeset (grap|pic|tbl|eqn|troff -mpm) in Times and Courier by the authors. Copyright  2003 by Robert Fourer, David M. Gay and Brian Kernighan. All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording, or otherwise, without the prior written permission of the publisher. Printed in the United States of America. Published simultaneously in Canada.
    About the authors: Robert Fourer received his Ph.D. in operations research from Stanford University in 1980, and is an active researcher in mathematical programming and modeling language design. He joined the Department of Industrial Engineering and Management Sciences at Northwestern University in 1979, and served as chair of the department from 1989 to 1995. David M. Gay received his Ph.D. in computer science from Cornell University in 1975, and was in the Computing Science Research Center at Bell Laboratories from 1981 to 2001; he is now CEO of AMPL Optimization LLC. His research interests include numerical analysis, optimization, and scientific computing. Brian Kernighan received his Ph.D. in electrical engineering from Princeton University in 1969. He was in the Computing Science Research Center at Bell Laboratories from 1969 to 2000, and now teaches in the Computer Science department at Princeton. He is the co-author of several computer science books, including The C Programming Language and The UNIX Programming Environment.
    ________________________________________________________________________ ________________________ Contents Introduction Chapter 1. Production Models: Maximizing Profits 1.1 A two-variable linear program 1.2 The two-variable linear program in AMPL 1.3 A linear programming model 1.4 The linear programming model in AMPL The basic model An improved model Catching errors 1.5 Adding lower bounds to the model 1.6 Adding resource constraints to the model 1.7 AMPL interfaces Chapter 2. Diet and Other Input Models: Minimizing Costs 2.1 A linear program for the diet problem 2.2 An AMPL model for the diet problem 2.3 Using the AMPL diet model 2.4 Generalizations to blending, economics and scheduling Chapter 3. Transportation and Assignment Models 3.1 A linear program for the transportation problem 3.2 An AMPL model for the transportation problem 3.3 Other interpretations of the transportation model Chapter 4. Building Larger Models 4.1 A multicommodity transportation model 4.2 A multiperiod production model 4.3 A model of production and transportation Chapter 5. Simple Sets and Indexing 5.1 Unordered sets vii xv 1 2 5 6 7 8 10 12 13 15 18 27 27 30 32 37 43 44 45 49 55 56 59 63 73 73
    viii AMPL: A MODELING LANGUAGE FOR MATHEMATICAL PROGRAMMING 5.2 Sets of numbers 5.3 Set operations 5.4 Set membership operations and functions 5.5 Indexing expressions 5.6 Ordered sets Predefined sets and interval expressions Chapter 6. Compound Sets and Indexing 6.1 Sets of ordered pairs 6.2 Subsets and slices of ordered pairs 6.3 Sets of longer tuples 6.4 Operations on sets of tuples 6.5 Indexed collections of sets Chapter 7. Parameters and Expressions 7.1 Parameter declarations 7.2 Arithmetic expressions 7.3 Logical and conditional expressions 7.4 Restrictions on parameters 7.5 Computed parameters 7.6 Randomly generated parameters 7.7 Logical parameters 7.8 Symbolic parameters Chapter 8. Linear Programs: Variables, Objectives and Constraints 8.1 Variables 8.2 Linear expressions 8.3 Objectives 8.4 Constraints Chapter 9. Specifying Data 9.1 Formatted data: the data command 9.2 Data in lists Lists of one-dimensional sets and parameters Lists of two-dimensional sets and parameters Lists of higher-dimensional sets and parameters Combined lists of sets and parameters 9.3 Data in tables Two-dimensional tables Two-dimensional slices of higher-dimensional data Higher-dimensional tables Choice of format 9.4 Other features of data statements Default values Indexed collections of sets Initial values for variables 75 76 78 79 82 86 91 91 93 96 98 100 109 110 111 114 116 118 121 122 123 129 129 132 134 137 143 143 145 145 146 148 151 154 154 156 157 159 160 160 161 162
    AMPL: A MODELING LANGUAGE FOR MATHEMATICAL PROGRAMMING 9.5 Reading unformatted data: the read command Chapter 10. Database Access 10.1 General principles of data correspondence 10.2 Examples of table-handling statements 10.3 Reading data from relational tables Reading parameters only Reading a set and parameters Establishing correspondences Reading other values 10.4 Writing data to relational tables Writing rows inferred from the data specifications Writing rows inferred from a key specification 10.5 Reading and writing the same table Reading and writing using two table declarations Reading and writing using the same table declaration 10.6 Indexed collections of tables and columns Indexed collections of tables Indexed collections of data columns 10.7 Standard and built-in table handlers Using the standard ODBC table handler Using the standard ODBC table handler with Access and Excel Built-in table handlers for text and binary files Chapter 11. Modeling Commands 11.1 General principles of commands and options Commands Options 11.2 Setting up and solving models and data Entering models and data Solving a model 11.3 Modifying data Resetting Resampling The let command 11.4 Modifying models Removing or redefining model components Changing the model: fix, unfix; drop, restore Relaxing integrality Chapter 12. Display Commands 12.1 Browsing through results: the display command Displaying sets Displaying parameters and variables Displaying indexed expressions 12.2 Formatting options for display ix 163 169 169 174 180 180 182 184 185 186 186 189 191 192 193 193 193 196 197 198 200 201 203 203 204 204 206 206 207 209 209 209 210 212 213 214 215 219 219 220 220 224 227
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