Handle finite disjunct constraints in an InfiniteGDP model for MBM

[dnguyen227]

While sampling M values for InfGDP problems, the possibility of finite disjunction constraints was not considered. Small fix applied here.

using DisjunctiveProgramming, InfiniteOpt, HiGHS
model = InfiniteGDPModel(HiGHS.Optimizer)
@infinite_parameter(model, t in [0, 1], num_supports = 11)
@variable(model, 0 <= x <= 10, Infinite(t))   # operating variable
@variable(model, 0 <= d <= 10)                # design variable
@variable(model, Y[1:2], Logical)

@constraint(model, x >= 1 - t)
@constraint(model, d >= 3, Disjunct(Y[1]))    # finite: no infinite variable
@constraint(model, d >= 5, Disjunct(Y[2]))
@disjunction(model, Y)
@objective(model, Min, d + ∫(x, t))

optimize!(model, gdp_method = MBM(HiGHS.Optimizer))

Upon running you'd get

Unrecognized sampler value ExhaustiveSampler() for MBM on an infinite model

,

[codecov]

Codecov Report

✅ All modified and coverable lines are covered by tests.
✅ Project coverage is 99.69%. Comparing base (eca397e) to head (be8e24b).

Additional details and impacted files

@@           Coverage Diff           @@
##           master     #146   +/-   ##
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  Coverage   99.69%   99.69%           
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  Files          21       21           
  Lines        2265     2267    +2     
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+ Hits         2258     2260    +2     
  Misses          7        7           

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[dnguyen227]

@pulsipher ready for review

[pulsipher]

Please merge with main to get to resolve conflicts