Resource allocation in a collaborative reforestation value chain: Optimisation with multi-objective models

Area of Science:

• Ecology
• Operations Research
• Forestry Management

Background:

• Reforestation success hinges on selecting appropriate seeds tailored to specific site conditions.
• Complex value chains with multiple partners complicate efficient seed allocation.
• Existing seed allocation methods often overlook ecological parameters and partner collaboration.

Purpose of the Study:

• To develop and apply multi-objective optimization models for seed allocation in a collaborative, make-to-order reforestation value chain.
• To identify optimal seed-site compatibility to enhance regeneration success.
• To balance reforestation goals with the objectives of diverse partners (seed center, nurseries).

Main Methods:

• Development of multi-objective optimization models for seed allocation.
• Application of the lexicographic method to solve the models.
• Case study analysis within the Quebec reforestation value chain.

Main Results:

• Optimal seed allocation solutions favoring reforestation success were identified.
• Integrating partner objectives significantly modified initial allocation plans.
• Simultaneous consideration of partner objectives altered allocation based on priority without compromising reforestation success.

Conclusions:

• The proposed models offer decision-makers a tool for effective seed allocation planning.
• The models support reforestation success while considering partner satisfaction and value chain constraints.
• This research contributes a sustainable seed allocation model encompassing ecological, economic, and social sustainability pillars.