From a combinatorics perspective, what if what you are requiring of the optimization algorithm is too scattered?
In other words, from a combinatorics perspective, what if what you are requiring in terms of the optimization problem specification, also referring to the constraints, including equality constraints, implies too scattered and sparse coefficient (variable cell) ranges.
Is this possible? The algorithm may then struggle to locate the feasible regions or ranges.
I am particularly referring to a nonconvex nonlinear optimization problem.
Hi Brian,
I suggest you explore the connections between discrete variational Hamiltonian mechanics and global non-convex optimization by following jointly:
- Lall et al., " Discrete variational Hamiltonian mechanics ", 2006 - http://lall.stanford.edu/papers/lall_2006b_jphysa_discrete_hamiltonians_2006_04_24_01/pubdata/entry.pdf
- Gao et al., " Canonical Duality Theory: Connections between Nonconvex Mechanics and Global Optimization ", 2009 -
Chapter Canonical Duality Theory: Connections between Nonconvex Mech...
Regards
My suggested solution is directly in relation with your additional question https://www.researchgate.net/post/Do_nested_optimization_problems_exist
Do you have bounded, e.g. binary, variables or unbounded ones. I the case of unbounded variables, the problem may not have an algorithm.
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