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Supply-chain network design via simulation, optimization, and greenfield analysis.
Tools
11
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Last checked
28h ago
Tools & capabilities
11 toolsRead from the running server on 28h ago.
describe_greenfield_demo
read-only
demo_id*
Full detail on one greenfield demo — region, customer count, available dc_count values, and the score-curve elbow finding. Use this before get_greenfield_result to know what dc_cou… Full detail on one greenfield demo — region, customer count, available dc_count values, and the score-curve elbow finding. Use this before get_greenfield_result to know what dc_count values are precomputed.
describe_opt_demo
read-only
demo_id*
Full detail on one optimization demo — controls, available scenario keys, sites, fixed parameters, citations, and the key finding the demo illustrates. Use this before get_opt_resu… Full detail on one optimization demo — controls, available scenario keys, sites, fixed parameters, citations, and the key finding the demo illustrates. Use this before get_opt_result to know what scenario_key values are accepted.
explain_greenfield
read-only
Reference text on greenfield analysis — clean-slate facility-location math. Covers the weighted center-of-gravity (Weber) formulation, Weiszfeld's iterative algorithm, Lloyd's-styl… Reference text on greenfield analysis — clean-slate facility-location math. Covers the weighted center-of-gravity (Weber) formulation, Weiszfeld's iterative algorithm, Lloyd's-style alternating location-allocation for N facilities, service constraints (% demand vs % customers within a distance band), and the inverse problem of solving for minimum N. Also covers when to use greenfield vs facility selection (the open/close MIP). Pure static text — no engine call, deterministic output. Use this when the user asks a conceptual 'how does greenfield analysis work' or 'where would I put my DCs' question. ChiAha's GreenfieldAnalysis engine powers the US Greenfield Design demo on the sandbox.
explain_optimization
read-only
Reference text on supply-chain network optimization — mixed-integer programming (MIP), the structure of decision variables and constraints, the objective function for landed-cost m… Reference text on supply-chain network optimization — mixed-integer programming (MIP), the structure of decision variables and constraints, the objective function for landed-cost minimization, and the common problem classes (facility selection, sourcing, flow constraints, multi-period, BOM/production, multi-objective). Also covers when to reach for optimization vs simulation. Pure static text — no engine call, deterministic output. Use this when the user asks a conceptual 'how does network optimization work' question. ChiAha's AMOS optimizer (open-source, Odin, GLOP/CBC via OR-Tools) powers the Tariff and Coffee Co-pack demos on the sandbox.
get_greenfield_result
read-only
demo_id*dc_count*
Get the precomputed result for one DC count of a greenfield demo. Returns sited DCs (lat/lon + city/state, nearest-city snapped), customer-to-DC assignments, and the score for that… Get the precomputed result for one DC count of a greenfield demo. Returns sited DCs (lat/lon + city/state, nearest-city snapped), customer-to-DC assignments, and the score for that DC count. ANTI-FABRICATION: every result is verbatim engine output from greenfield-cli — quote them in your reply, do not round or fabricate cities.
get_opt_result
read-only
demo_id*scenario_key
Get the precomputed result for one scenario of an optimization demo. Returns the verbatim engine output JSON (AMOS for tariff/coffee, SSO output for sso-basic) including the optima… Get the precomputed result for one scenario of an optimization demo. Returns the verbatim engine output JSON (AMOS for tariff/coffee, SSO output for sso-basic) including the optimal sourcing/production/transport decisions, costs, and any open/close facility variables. ANTI-FABRICATION: every numeric result is verbatim from the optimization engine that ran offline — quote them in your reply, do not round or recompute. Call describe_opt_demo first to learn valid scenario_key formats for each demo.
get_sc_theory
read-only
Reference guide to supply-chain simulation concepts: ordering policies, BOM, FDD formulas, event-driven simulation. Pure static text — no engine call, deterministic output. Use thi… Reference guide to supply-chain simulation concepts: ordering policies, BOM, FDD formulas, event-driven simulation. Pure static text — no engine call, deterministic output. Use this when the user asks a conceptual 'how does this work' question rather than asking for a number.
list_greenfield_demos
read-only
List the bundled SCModeling greenfield demos. Returns id + label + one-line summary. Currently one demo (US, 189 customer points). Use this before describe_greenfield_demo or get_g… List the bundled SCModeling greenfield demos. Returns id + label + one-line summary. Currently one demo (US, 189 customer points). Use this before describe_greenfield_demo or get_greenfield_result.
list_models
read-only
List the bundled SCModeling sample supply-chain models. Returns a catalog with each model's id and a short description. Use this before run_simulation to know which model_id values… List the bundled SCModeling sample supply-chain models. Returns a catalog with each model's id and a short description. Use this before run_simulation to know which model_id values are valid.
list_opt_demos
read-only
List the bundled SCModeling optimization demos. Returns id + label + one-line summary for each (Tariff, Coffee Co-pack, SSO Basic). Use this before describe_opt_demo or get_opt_res… List the bundled SCModeling optimization demos. Returns id + label + one-line summary for each (Tariff, Coffee Co-pack, SSO Basic). Use this before describe_opt_demo or get_opt_result to know which demo_id values are valid. All demos are precomputed sample-only fixtures — for optimization on real client data, the SCModeling desktop tool is the product.
run_simulation
read-only
model_id*