[Pyomo.DoE] Add simultaneous design of multiple experiments

[smondal13]

Fixes # .

Summary/Motivation:

This PR adds a new DesignOfExperiments.optimize_experiments() API in pyomo/contrib/doe/doe.py to support simultaneous optimization of multiple experiments in one workflow. The motivation is to provide a multi-experiment DoE interface with stronger initialization options, clearer mode handling (template vs. user-initialized experiments), and richer diagnostics/results than the existing single-experiment path.

Changes proposed in this PR:

• Added API optimize_experiments() for multi-experiment DoE optimization.
• Added Cholesky-based D- and A-optimality objective and Greybox-based D-, A-, E-, and ME- optimality objective
• Implemented two operating modes:
  • Template mode: pass one experiment and set n_exp.
  • User-initialized mode: pass a list of experiments; n_exp is inferred/validated.
• Added optional LHS-based initialization (initialization_method="lhs") with controls for:
  • sample count, seed, candidate evaluation parallelism, combination fim metric scoring parallelism,
  • worker count, chunk size, parallel threshold, and optional wall-clock budget.
• Added symmetry-breaking constraints for multi-experiment solves:
  • supports user-specified variable through sym_break_cons suffix,
  • falls back to the first experiment input with a diagnostic warning when not provided.
• Expanded output for this API:
  • per-scenario and per-experiment results (designs, outputs, measurement errors, FIM/sensitivities),
  • aggregated FIM metrics, timings, settings, names, diagnostics, and structured run_info.
• Added JSON-safe serialization via _DoEResultsJSONEncoder for numpy/Pyomo-enum values when writing results_file.

Note:

• Added new documentation.md which describes the API. This documentation is to help the reviewers to understand the API and will not be merged into Pyomo:main

Remove before merging

• documentation.md
• rb_multi.py

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[blnicho]

@smondal13 here is my next set of comments. I have 2 more files to look at.

[smondal13]

@blnicho I have removed _initialize_cholesky_from_fim() and consolidated the shared FIM-derived initialization updates into _initialize_standard_objective_block(). Both the single- and multi-experiment designs were doing the same initialization work (L, L_inv, fim_inv, cov_trace, determinant/pseudo-trace state), so consolidating that logic avoids duplication and reduces the risk of the two paths drifting out of sync.

[smondal13]

@blnicho @mrmundt can you run this again? It is showing the gjh failure