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ty for answering.

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1st, Integer Linear Programming, some or all of the decision variables are required to take integer values.

2. Mixed integer Linear Programming, some variables are required to take integer values while others are allowed to be continues.

3.Binary Linear Programming, restricts variables to take binary values (0 or 1). It's often used to model decision making problems with yes/no choices.

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Network Flow Problems

Multi-Objective Linear Programming

Stochastic Linear Programming


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  • Production planning: Linear programming can be used to determine the optimal production levels for a factory, given the costs of production, the demand for the products, and the availability of resources.


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Four special cases and difficulties arise at times when using the graphical approach to solving LP problems

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calculating the “optimal” production levels to maximize profits, given the restrictions of supplies and personnel.

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Linear programming (LP) is a mathematical technique used to optimize a linear objective function subject to linear constraints. There are several special cases and variations of linear programming that have specific characteristics and applications. Here are some examples: Integer Linear Programming (ILP): Binary Linear Programming: Mixed Integer Linear Programming (MILP): Fractional Linear Programming: Network Flow Problems:


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Special cases or variations of linear programming include:

  1. Integer Linear Programming (ILP)

  2. Binary Linear Programming

  3. Mixed Integer Linear Programming (MILP)

  4. Multi-Objective Linear Programming (MOLP)

  5. Stochastic Linear Programming

  6. Degeneracy

  7. Unboundedness

  8. Infeasibility

  9. Redundant Constraints

  10. Network Flow Problems

  11. Assignment Problems


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Integer learning programming has the decision variables are constrained to take only integers values. It can be used in situations like production quantities and project scheduling

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Binary Linear Programming, restricts variables to take binary values (0 or 1). It's often used to model decision making problems with yes/no choices.

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