Date of Award

2019

Publication Type

Master Thesis

Degree Name

M.Sc.

Department

Computer Science

First Advisor

Jessica Chen

Keywords

Cluster Hiring, Data Mining, ILP, Social Network, Team formation

Rights

info:eu-repo/semantics/openAccess

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Abstract

Given a set of projects, each requiring a set of specific skills, and given a set of experts, each possessing a set of specific skills, the cluster hire in a network of experts seeks to find a suitable subset of the experts to jointly accomplish a subset of the given projects with their complementary expertise. We consider the problem of selecting an optimal team of the experts in terms of maximizing the profit that the selected team is able to generate, where the profit is determined partly by the revenue of the projects this team is able to accomplish, partly by the efficiency of the team measured by the prior collaboration experience among its team members. This optimization is further constrained by the given workload capacity of each expert, and by a given budget on team hiring. We approach the optimal solution with Integer Linear Programming (ILP) technique and compare its result with those from other heuristic solutions.

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