Designing a generic human-machine framework for real-time supply chain planning

Abstract

Abstract Mixed-Initiative-Systems (MIS) are hybrid decision-making systems in which human and machine collaborate in order to produce a solution. This paper described an MIS adapted to business optimization problems. These problems can usually be solved in less than an hour as they show a linear structure. However, this delay is unacceptable for iterative and interactive decision-making contexts where users need to provide their input. Therefore, we propose a system providing the decision-makers with a convex hull of optimal solutions that minimize/maximize the variables of interest. The users can interactively modify the value of a variable and the system is able to recompute a new optimal solution in a few milliseconds. Four real-time reoptimization methods are described and evaluated. We also propose an improvement to this basic scheme in order to allow a user to explore near-optimal solutions as well. Examples showing real case of how we have exploited this framework within interactive decision support software are given. Highlights A Mixed Initiative System adapted to business optimization problems is presented. Real-time reoptimization methods are described and evaluated. The system is able to recompute a new optimal solution in a few milliseconds. Improvement to this basic scheme allow a user to explore near-optimal solutions. Examples showing real case of exploiting this framework are given.