An efficient metaheuristic for integrated scheduling and staffing IT projects based on a generalized minimum cost flow network

Rainer Kolisch, Christian Heimerl

Research output: Contribution to journalArticlepeer-review

33 Scopus citations

Abstract

Scheduling IT projects and assigning the project work to human resources are an important and common tasks in almost any IT service company. It is particularly complex because human resources usually have multiple skills. Up to now only little work has considered IT-specific properties of the project structure and human resources. In this article, we present an optimization model that simultaneously schedules the activities of multiple IT projects with serial network structures and assigns the project work to multiskilled internal and external human resources with different efficiencies. The goal is to minimize costs. We introduce a metaheuristic that decomposes the problem into a binary scheduling problem and a continuous staffing problem where the latter is solved efficiently by exploiting its underlying network structure. For comparison, we solve the mixed-binary linear program with a state-of-the-art commercial solver. The impacts of problem parameters on computation time and solution gaps between the metaheuristic and the solver are assessed in an experimental study. Our results show that the metaheuristic provides very favorable results in considerable less time than the solver for midsize problems. For larger problems, it shows a similar performance while the solver fails to return feasible solutions. © 2012 Wiley Periodicals, Inc. Naval Research Logistics 59: 111-127, 2012

Original languageEnglish
Pages (from-to)111-127
Number of pages17
JournalNaval Research Logistics
Volume59
Issue number2
DOIs
StatePublished - Mar 2012

Keywords

  • generalized minimum cost flow
  • genetic algorithm
  • metaheuristic
  • multiskilled resources
  • project scheduling
  • project staffing
  • resource assignment
  • tabu search

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