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This set arises as a subproblem of more general mixed integer problems such as inventory routing and facility location problems.
As the number of plies is restricted to integer values, the optimization problem considered belongs to the class of non-linear mixed integer problems (NMIP).
Such set arises as a relaxation of feasible sets of general mixed integer problems such as lot-sizing and network design problems.
ACOmi (Ant Colony Optization for mixed integer problems) is an extension of the ant colony optimization metaheuristic that enables to handle mixed integer variable search domains.
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The problem is solved by formulating a nonlinear, stochastic mixed integer problem.
Because the UC/ED problem is nonlinear, non-convex and mixed integer problem, the MPC must be used as nonlinear.
The proposed model is a mixed integer problem with non-linear constraints known to be NP-hard.
This allows the hydrothermal scheduling problem to become an ordinary mixed integer problem that can be solved by using standard commercial mixed integer programming solvers.
The mathematical nature of this optimization problem, a nonlinear mixed integer problem, is at the origin of a multitude of contributions to the literature in the last 25 years.
We propose a mathematical model and develop a heuristic procedure based on a genetic algorithm to solve the corresponding mixed integer problem.
Moreover, the idea of local grid refinement is proposed to eliminate the mixed integer problem of well placement.
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