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A Heuristic Algorithm for Optimizing Business Matchmaking Scheduling

Author

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  • Yingping Huang

    (Department of Computer Science and Information Systems, College of Business, University of North Alabama, Florence, AL, USA)

  • Xihui Zhang

    (Department of Computer Science and Information Systems, College of Business, University of North Alabama, Florence, AL, USA)

  • Paulette S. Alexander

    (Department of Computer Science and Information Systems, College of Business, University of North Alabama, Florence, AL, USA)

Abstract

Business matchmaking is a service dedicated to providing one-on-one appointments for small businesses (or sellers) to meet with government agencies and large corporations (or buyers) for contracting opportunities. Business matchmaking scheduling seeks to maximize the total number of appointments with the maximum objective that weighs the preferences of both buyers and sellers. In this paper, the authors transformed the business matchmaking scheduling problem into a 3-dimensional planar assignment problem and solved it heuristically using a series of bipartite maximum weighted maximum cardinality matching problems. Simulation experiments and real data showed that this algorithm outperforms human experts and prior algorithm in terms of number of appointments, the objective that weighs buyer and seller’s preferences, and the execution time.

Suggested Citation

  • Yingping Huang & Xihui Zhang & Paulette S. Alexander, 2012. "A Heuristic Algorithm for Optimizing Business Matchmaking Scheduling," International Journal of Operations Research and Information Systems (IJORIS), IGI Global, vol. 3(4), pages 59-73, October.
    • Handle: RePEc:igg:joris0:v:3:y:2012:i:4:p:59-73
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    Cited by:

    1. Vangerven, Bart & Ficker, Annette M.C. & Goossens, Dries R. & Passchyn, Ward & Spieksma, Frits C.R. & Woeginger, Gerhard J., 2018. "Conference scheduling — A personalized approach," Omega, Elsevier, vol. 81(C), pages 38-47.
    2. Braathen, Christian, 2022. "Interview Scheduling: An Integer Programming Approach," Discussion Papers 2022/10, Norwegian School of Economics, Department of Business and Management Science.

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