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An empirical comparison of heuristic and graph theoretic methods for creating maximally diverse groups, VLSI design, and exam scheduling

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  • Weitz, R. R.
  • Lakshminarayanan, S.

Abstract

Creating groups of maximum diversity, VLSI design (where the objective is to group highly connected modules onto the same circuit), and the final exam scheduling task of assigning exam blocks to exam days, are all mathematically equivalent. VLSI design and exam scheduling are clearly important problems. Forming maximally diverse groups, based upon multiple criteria, has immediate application in academic or training settings where it may be desired to create class sections, or project groups within classes, such that students are immersed in a diverse environment. This research empirically contrasts graph theoretic approaches drawn from VLSI design with heuristics originating from final exam scheduling and the maximum diversity group problem. The methods are tested on a 'real-world' data set and evaluated on the criteria of solution quality and computational resources required. A principal conclusion of this work is that an adaptation of a pair-wise exchange procedure drawn from the final exam scheduling literature outperforms a more sophisticated graph theoretic approach which has previously been shown to be a top performer for VLSI design.

Suggested Citation

  • Weitz, R. R. & Lakshminarayanan, S., 1997. "An empirical comparison of heuristic and graph theoretic methods for creating maximally diverse groups, VLSI design, and exam scheduling," Omega, Elsevier, vol. 25(4), pages 473-482, August.
  • Handle: RePEc:eee:jomega:v:25:y:1997:i:4:p:473-482
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    References listed on IDEAS

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    Cited by:

    1. Lai, Xiangjing & Hao, Jin-Kao, 2016. "Iterated maxima search for the maximally diverse grouping problem," European Journal of Operational Research, Elsevier, vol. 254(3), pages 780-800.
    2. Yang, Xiao & Cai, Zonghui & Jin, Ting & Tang, Zheng & Gao, Shangce, 2022. "A three-phase search approach with dynamic population size for solving the maximally diverse grouping problem," European Journal of Operational Research, Elsevier, vol. 302(3), pages 925-953.
    3. Bhadury, Joyendu & Mighty, E. Joy & Damar, Hario, 2000. "Maximizing workforce diversity in project teams: a network flow approach," Omega, Elsevier, vol. 28(2), pages 143-153, April.
    4. Saber, Hussein M. & Ghosh, Jay B., 2001. "Assigning students to academic majors," Omega, Elsevier, vol. 29(6), pages 513-523, December.
    5. T. Godwin, 2022. "Obtaining quality business school examination timetable under heterogeneous elective selections through surrogacy," OPSEARCH, Springer;Operational Research Society of India, vol. 59(3), pages 1055-1093, September.
    6. Şenay Ağca & Burak Eksioglu & Jay B. Ghosh, 2000. "Lagrangian solution of maximum dispersion problems," Naval Research Logistics (NRL), John Wiley & Sons, vol. 47(2), pages 97-114, March.
    7. Lai, Xiangjing & Hao, Jin-Kao & Fu, Zhang-Hua & Yue, Dong, 2021. "Neighborhood decomposition based variable neighborhood search and tabu search for maximally diverse grouping," European Journal of Operational Research, Elsevier, vol. 289(3), pages 1067-1086.
    8. Arne Schulz, 2022. "A new mixed-integer programming formulation for the maximally diverse grouping problem with attribute values," Annals of Operations Research, Springer, vol. 318(1), pages 501-530, November.
    9. Kayse Lee Maass & Vera Mann Hey Lo & Anna Weiss & Mark S. Daskin, 2015. "Maximizing Diversity in the Engineering Global Leadership Cultural Families," Interfaces, INFORMS, vol. 45(4), pages 293-304, August.
    10. Turabieh, Hamza & Abdullah, Salwani, 2011. "An integrated hybrid approach to the examination timetabling problem," Omega, Elsevier, vol. 39(6), pages 598-607, December.

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