Decision support for sustainable forest harvest planning using multi-scenario multiobjective robust optimization

TL;DR

This paper introduces a novel multi-scenario multiobjective robust optimization approach for sustainable forest harvest planning, enabling decision-makers to analyze trade-offs and uncertainties in short-term forest management.

Contribution

It presents a new interactive decision-support method with a multi-scenario multiobjective mixed-integer model for robust forest harvest scheduling over multiple periods.

Findings

Supports trade-off analysis between demand satisfaction and objectives.

Provides robust solutions accounting for uncertainties in planning.

Validated with a case study on Swedish forest stands.

Abstract

Sustainable forest management requires handling uncertainty introduced from various sources, considering different conflicting economic, environmental, and social objectives, and involving multiple decision-making periods. This study proposes an interactive and intuitive decision-support approach for sustainable, robust forest harvest scheduling in multiple periods in a short-term (6-12 months) planning horizon. The approach includes a novel multi-scenario multiobjective mixed-integer optimization problem that allows forest planners to separately study the trade-offs between demand satisfactions for multiple assortments in different planning periods. Moreover, it provides an intuitive robust analysis to support forest planners in dealing with uncertainty and investigating potential variations of the outcomes as the consequences of uncertainty in tactical forest planning problems. We validate the proposed decision-support approach in a Swedish case study with 250 forest stands, three assortments (pine, spruce, deciduous trees), and a twelve-month harvest planning horizon. We demonstrate how the proposed approach supports a forest practitioner in trade-offs and robust analyses and finding the most preferred robust solution.