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Scatter search for trainees to software project requirements stable allocation

Author

Listed:
  • Mangesh Gharote

    () (IIT Bombay
    TATA Consultancy Services Limited)

  • Rahul Patil

    () (IIT Bombay)

  • Sachin Lodha

    () (TATA Consultancy Services Limited)

Abstract

Abstract In this paper, we study a centralized, stable matching scheme, which allocates trainees to software project requirements, to minimize retraining and relocation costs when the preference lists of the project requirements may contain ties of arbitrary lengths. This particular trainees’ assignment problem is important because the allocation decisions not only influence the costs but also impact software project deliverables and intern attrition rates. It is also an NP-hard problem because of the inclusion of the ties, and the costs in the stable allocation model. We, therefore, have designed a GRASP-based scatter search method, to solve the large size instances of our assignment problem efficiently. The GRASP method uses randomized algorithms to generate initial trial solutions. A repair heuristic based on regret minimization idea is designed to convert an unstable solution to a stable solution during an improvement phase. Computational experiments suggest that the proposed algorithm significantly reduces run time compared to the CPLEX, and produces solutions that are at an average 4.5% away from the best CPLEX solutions for the large size problem instances. Moreover, our scatter search method consistently provides better quality solutions than the two state of the art methods from the prior literature.

Suggested Citation

  • Mangesh Gharote & Rahul Patil & Sachin Lodha, 2017. "Scatter search for trainees to software project requirements stable allocation," Journal of Heuristics, Springer, vol. 23(4), pages 257-283, August.
  • Handle: RePEc:spr:joheur:v:23:y:2017:i:4:d:10.1007_s10732-017-9343-z
    DOI: 10.1007/s10732-017-9343-z
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    References listed on IDEAS

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    1. Maenhout, Broos & Vanhoucke, Mario, 2010. "A hybrid scatter search heuristic for personalized crew rostering in the airline industry," European Journal of Operational Research, Elsevier, vol. 206(1), pages 155-167, October.
    2. Yagiura, Mutsunori & Ibaraki, Toshihide & Glover, Fred, 2006. "A path relinking approach with ejection chains for the generalized assignment problem," European Journal of Operational Research, Elsevier, vol. 169(2), pages 548-569, March.
    3. Russell, Robert A. & Chiang, Wen-Chyuan, 2006. "Scatter search for the vehicle routing problem with time windows," European Journal of Operational Research, Elsevier, vol. 169(2), pages 606-622, March.
    4. B. Maenhout & M. Vanhoucke, 2007. "A Hybrid Scatter Search Heuristic for Personalized Crew Rostering in the Airline Industry," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 07/454, Ghent University, Faculty of Economics and Business Administration.
    5. Zaraket, Fadi A. & Olleik, Majd & Yassine, Ali A., 2014. "Skill-based framework for optimal software project selection and resource allocation," European Journal of Operational Research, Elsevier, vol. 234(1), pages 308-318.
    6. González, Miguel A. & Vela, Camino R. & Varela, Ramiro, 2015. "Scatter search with path relinking for the flexible job shop scheduling problem," European Journal of Operational Research, Elsevier, vol. 245(1), pages 35-45.
    7. Kothari, Ravi & Ghosh, Diptesh, 2012. "Scatter Search Algorithms for the Single Row Facility Layout Problem," IIMA Working Papers WP2012-04-01, Indian Institute of Management Ahmedabad, Research and Publication Department.
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