CPLEX

 1. General information

      1.1. Features

 2. How to use

 3. Benchmark

 4. More information

1. General information

IBM ILOG CPLEX Optimizer’s mathematical optimization technology enables smarter decision-making for efficient resource utilization. CPLEX provides robust algorithms for demanding problems: IBM ILOG CPLEX Optimizer has solved problems with millions of constraints and variables. 12.6.3 version.

1.1. Features

  • Automatic and dynamic algorithm parameter control
    IBM ILOG CPLEX Optimizer automatically determines “smart” settings for a wide range of algorithm parameters, usually resulting in optimal linear programming solution performance. However, for a more hands-on approach, dozens of parameters may be manually adjusted, including algorithmic strategy controls, output information controls, optimization duration limits, and numerical tolerances.
  • Fast, automatic restarts from an advanced basis
    Large problems can be modified, and then solved again in a fraction of the original solution time.
  • A variety of problem modification options, such as:
    – The ability to add and delete variables
    – The ability to add and delete constraints
    – The ability to modify objective, right-hand side, bound and matrix coefficients
    – The ability to change constraint types
  • A wide variety of input/output options, such as:
    – Problem files: read/write MPS files, IBM ILOG CPLEX Optimizer LP files, MPS basis and revise files, binary problem/basis files
    – Log files: session information and various solution reports
    – Solution files: ASCII and binary solution files
    – IBM ILOG CPLEX Optimizer messages: Each message type (such as RESULTS, WARNINGS or ERRORS) can be directed to specified files, or completely suppressed.
  • Post solution information and analysis, including:
    – Objective function value
    – Solution variable and slack values
    – Constraint dual values (shadow prices)
    – Variable reduced costs
    – Right-hand side, objective function, and bound sensitivity ranges
    – Basic variables and constraints
    – Solution infeasibilities (if any exist)
    – Iteration/node count, solution time, process data
    – Infeasibility (IIS) finder for diagnosing problem infeasibilities
    – Feasibility optimizer for automatic correction of infeasible models

2. How to use

To use CPLEX execute:

/software/bin/cplex/cplex

3. Benchmark

There is a small benchmark usingCOIN-OR, see COIN-OR web page.

4. More information

CPLEX web page.

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