Integer Programming

Integer Programming: Theory and Practice

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ISBN 9780849319143
Cat# 1914
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ISBN 9781420039597
Cat# E1914
 

Features

  • Contains invited, refereed articles that explore both theoretical aspects of integer programming as well as major applications
  • Introduces a new concept, structured separation, and details how it can be used in a decomposition framework to obtain bounds on the optimal value of solutions
  • Demonstrates the efficacy of strategic network models for flight scheduling via tests on the operations of a major airline
  • Develops integer-programming models to determine the optimal fleet mix and schedule for transportation of products
  • Details how a set-packing integer-programming model may be used to find data cycle map constructions that are feasible and efficient
  • Reviews eight publicly-available software packages used for MILP
  • Includes case studies that illustrate use of solver frameworks to develop custom solvers for specific problem classes
  • Summary

    Integer Programming: Theory and Practice contains refereed articles that explore both theoretical aspects of integer programming as well as major applications.

    This volume begins with a description of new constructive and iterative search methods for solving the Boolean optimization problem (BOOP). Following a review of recent developments on convergent Lagrangian techniques that use objective level-cut and domain-cut methods to solve separable nonlinear integer-programming problems, the book discusses the generalized assignment problem (GAP). The final theoretical chapter analyzes the use of decomposition methods to obtain bounds on the optimal value of solutions to integer linear-programming problems.

    The first application article contains models and solution algorithms for the rescheduling of airlines following the temporary closure of airports. The next chapters deal with the determination of an optimal mix of chartered and self-owned vessels needed to transport a product. The book then presents an application of integer programming that involves the capture, storage, and transmission of large quantities of data collected during testing scenarios involving military applications related to vehicles, medicine, equipment, missiles, and aircraft.

    The next article develops an integer linear-programming model to determine the assortment of products that must be carried by stores within a retail chain to maximize profit, and the final article contains an overview of noncommercial software tools for the solution of mixed-integer linear programs (MILP). The authors purposefully include applications and theory that are usually not found in contributed books in order to appeal to a wide variety of researchers and practitioners.

    Table of Contents

    New Heuristics and Adaptive Memory Procedures for
    Boolean Optimization Problems, Lars M. Hvattum, Arne Løkketangen, and Fred Glover

    Convergent Lagrangian Methods for Separable Nonlinear
    Integer Programming: Objective Level-Cut and
    Domain-Cut Methods, Duan Li, Xiaoling Sun, and Jun Wang

    The Generalized Assignment Problem, Robert M. Nauss

    Decomposition in Integer Linear Programming, Ted K. Ralphs and Matthew V. Galati

    Airline Scheduling Models and Solution Algorithms
    for the Temporary Closure of Airports, Shangyao Yan and Chung-Gee Lin

    Determining an Optimal Fleet Mix and Schedules:
    Part I - Single Source and Destination, Hanif D. Sherali and Salem M. Al-Yakoob

    Determining an Optimal Fleet Mix and Schedules:
    Part II - Multiple Sources and Destinations, and the
    Option of Leasing Transshipment Depots, Hanif D. Sherali and Salem M. Al-Yakoob

    An Integer Programming Model for the Optimization
    of Data Cycle Maps, David Panton, Maria John, and Andrew Mason

    Application of Column-Generation Techniques to Retail
    Assortment Planning, Govind P. Daruka and Udatta S. Palekar

    Noncommercial Software for Mixed-Integer Linear
    Programming, Jeff T. Linderoth and Ted K. Ralphs

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