Abstract
Mixed-initiative systems for interactive optimization allow the user to add preferences to find satisfactory solutions. Industries use them as decision-support tools in order to take into consideration unexpected events or characteristics not stated in the optimization model. We present a design of an interactive optimization system that allows users to quickly find a new optimal solution when the user changes the values of decision variables. It anticipates the actions of the user and precomputes the solutions that satisfy the preferences by using both the capacities of the optimization software and a novel custom technique based on the kernel of the constraint matrix. This system is tested on a softwood lumber-drying planning problem and returns promising results for future use in wood industries.
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