Cost-minimizing team hires with participation constraint

Area of Science:

• Computer Science
• Operations Research
• Artificial Intelligence

Background:

• Effective project completion relies on optimal team formation to cover required skills.
• Existing team formation models often do not account for individual expert participation constraints.

Purpose of the Study:

• To introduce and define the participation constrained team hire problem.
• To develop algorithms for minimizing overall compensation while ensuring all projects are covered by qualified experts.
• To address the NP-hard nature of the problem with efficient solutions.

Main Methods:

• An exact algorithm was designed for a special case where project numbers are within expert participation limits.
• Three novel approximate algorithms were developed for the general NP-hard participation constrained team hire problem.
• Extensive experimental studies on synthetic and real datasets were conducted for performance evaluation.

Main Results:

• The exact algorithm significantly outperformed brute-force methods and demonstrated practical effectiveness.
• The three approximate algorithms exhibited varied performance characteristics depending on problem facets.
• The study provides the first investigation into the participation constrained team hire problem.

Conclusions:

• The proposed algorithms offer effective solutions for the participation constrained team hire problem.
• The research contributes a novel problem formulation and algorithmic approaches to optimize team formation under constraints.
• Findings suggest distinct algorithmic strategies are beneficial for different aspects of the team hiring problem.