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Washington Natural Resources, Department of·Washington

Multi-Objective Optimization Sustainable Harvest Calculation

Closes 8/3/2026$300k – $600kRequest for InformationLogin required
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Description

The Washington State Department of Natural Resources (DNR) is seeking vendor input on approaches, costs, and schedules for developing a multi‑objective optimization (MOO) tool to calculate sustainable timber harvest levels on its eastern Washington trust lands. The RFI is informational only; DNR will use the responses to shape future procurement opportunities. Vendors must address eight modeling scenarios (aspatial and spatial, with/without disturbance dynamics), outline recommended methodologies, staffing, timelines, cost estimates, and discuss limitations and alternatives. Responses are due by August 3 2026. • Provide detailed methodology for each of the eight MOO scenarios, including NPV, forest‑resilience, and carbon objectives. • Deliver a step‑by‑step execution plan, staffing matrix, schedule (Gantt‑style), and cost breakdown for each scenario. • Discuss limitations, alternative approaches, and data requirements, and answer specific technical questions (e.g., handling wildfire disturbance, resilience metrics, deterministic harvest levels).

Attached files

Contact

Denise Roush‑Livingston(Solicitation Coordinator)

denise.roush‑[email protected]

(360) 870-4119

Key dates

Opened
6/26/2026
Questions due
7/16/2026
Closes
8/3/2026

Last updated

Details

Type
Request for Information
Industry
Consulting Services
NAICS
541618
Solicitation №
DNR RFI 26-16

Budget estimate

$300,000 – $600,000

No contract value is disclosed; however, based on the scope—development of a sophisticated multi‑objective optimization tool, staffing of senior modelers, GIS analysts, and foresters, plus data integration and documentation—a typical engagement of this nature for a state agency could range from $300,000 to $600,000. The lower bound assumes a lean team with limited custom software, while the upper bound reflects a larger team, extensive spatial analysis, and comprehensive deliverables.

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