partnersorter

Partnersorter is a class of methods and tools designed to assign partners for collaborative activities by sorting participants according to attributes, preferences, and constraints. It may be implemented as software, a framework, or a conceptual approach used in education, business, and event contexts.

Inputs typically include a roster of participants with features such as skills, roles, language, availability, past collaborations, and stated preferences. Constraints may specify one-to-one pairing limits, avoidance of certain pairings, or required language compatibility. The output is a set of partner pairings or groupings, potentially with rankings or scores to reflect the quality of each match. Systems may support single pairs or multi-person partnerships.

Common approaches use compatibility scores, preference rankings, or distance metrics to determine good matches. Algorithms range from greedy and heuristics to more formal optimization methods such as stable matching, maximum weight matching, or constraint programming. The choice of method often depends on group size, required guarantees (e.g., no participant paired with more than one partner), and available computation time.

Applications include pair programming and lab partner assignment in education, mentoring and onboarding programs in organizations, project team formation, language exchange and peer learning, and event networking where attendees are matched for conversations. Partnersorter can facilitate objective and repeatable pairing, though it may require ongoing updates as participants’ attributes or constraints change.

Considerations include privacy and data handling, potential bias in data or scoring, fairness and transparency of the matching process, and scalability to larger groups. See also: stable marriage problem and maximum weight matching.