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Scheduling Public Requests for Proposals: Models and Insights

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  • Janne Kettunen
  • Young Hoon Kwak

Abstract

We show that the schedule for contracting public procurements can impact the number of proposals and thereby the cost of procured services or products. This holds when the market for procurement contracts is not perfectly competitive, which is typically the case for large and costly public procurements. We formalize this previously unexplored operational level problem of scheduling procurement contracting and develop an optimization framework to solve it. For large problems we propose a hierarchical optimization heuristic. Furthermore, we develop heuristics that do not require solving optimization problems, such as (i) equal number with mixed cost scheduling heuristic and (ii) equal cost scheduling heuristic. We show that depending on the characteristics of the procurement contract scheduling problem either of these approaches provides nearly the same expected total procurement cost as the optimal schedule. We apply our optimization framework to the Florida Department of Transportation's procurement contracts scheduling problems. We show that the optimized schedules are expected to yield significant cost savings over the actual schedules employed in practice. Our results have implications for public policy suggesting that the fiscal stimulus funds are cost‐effective to allocate for many small projects instead of few large projects.

Suggested Citation

  • Janne Kettunen & Young Hoon Kwak, 2018. "Scheduling Public Requests for Proposals: Models and Insights," Production and Operations Management, Production and Operations Management Society, vol. 27(7), pages 1271-1290, July.
  • Handle: RePEc:bla:popmgt:v:27:y:2018:i:7:p:1271-1290
    DOI: 10.1111/poms.12868
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    Cited by:

    1. Dan Bumblauskas & Amy Igou & Salil Kalghatgi & Cole Wetzel, 2022. "Public Policy and Broader Applications for the Use of Text Analytics During Pandemics," Interfaces, INFORMS, vol. 52(6), pages 568-581, November.

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