A Heuristic Algorithm for Optimizing Business Matchmaking Scheduling

Yingping Huang, Xihui Zhang and Paulette S. Alexander
Additional contact information
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

International Journal of Operations Research and Information Systems (IJORIS), 2012, vol. 3, issue 4, 59-73

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.

Date: 2012
References: Add references at CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://services.igi-global.com/resolvedoi/resolve. ... 018/joris.2012100104 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:igg:joris0:v:3:y:2012:i:4:p:59-73

Access Statistics for this article

International Journal of Operations Research and Information Systems (IJORIS) is currently edited by John Wang

More articles in International Journal of Operations Research and Information Systems (IJORIS) from IGI Global
Bibliographic data for series maintained by Journal Editor ().