Why is ILP generally more complex and time-consuming to solve than standard LP problems?
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Non-Convex Solution Space: ILP involves integer constraints, leading to a non-convex solution space, making it harder to navigate and find optimal solutions.
Exponential Growth of Combinations: The number of possible combinations of integer solutions can grow exponentially with the number of variables, complicating the search process.
Branch-and-Bound and Cutting Planes: ILP requires more sophisticated algorithms like branch-and-bound and cutting planes, which involve iterative processes and additional computations compared to the simpler simplex method used for LP