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A priori orienteering with time windows and stochastic wait times at customers

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  • Zhang, Shu
  • Ohlmann, Jeffrey W.
  • Thomas, Barrett W.

Abstract

In the pharmaceutical industry, sales representatives visit doctors to inform them of their products and encourage them to become an active prescriber. On a daily basis, pharmaceutical sales representatives must decide which doctors to visit and the order to visit them. This situation motivates a problem we more generally refer to as a stochastic orienteering problem with time windows (SOPTW), in which a time window is associated with each customer and an uncertain wait time at a customer results from a queue of competing sales representatives. We develop a priori routes with the objective of maximizing expected sales. We operationalize the sales representative’s execution of the a priori route with relevant recourse actions and derive an analytical formula to compute the expected sales from an a priori tour. We tailor a variable neighborhood search heuristic to solve the problem. We demonstrate the value of modeling uncertainty by comparing the solutions to our model to solutions of a deterministic version using expected values of the associated random variables. We also compute an empirical upper bound on our solutions by solving deterministic instances corresponding to perfect information.

Suggested Citation

  • Zhang, Shu & Ohlmann, Jeffrey W. & Thomas, Barrett W., 2014. "A priori orienteering with time windows and stochastic wait times at customers," European Journal of Operational Research, Elsevier, vol. 239(1), pages 70-79.
    • Handle: RePEc:eee:ejores:v:239:y:2014:i:1:p:70-79
    DOI: 10.1016/j.ejor.2014.04.040
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    References listed on IDEAS

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    2. Verbeeck, C. & Vansteenwegen, P. & Aghezzaf, E.-H., 2016. "Solving the stochastic time-dependent orienteering problem with time windows," European Journal of Operational Research, Elsevier, vol. 255(3), pages 699-718.
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    7. Zhang, Shu & Ohlmann, Jeffrey W. & Thomas, Barrett W., 2020. "Multi-period orienteering with uncertain adoption likelihood and waiting at customers," European Journal of Operational Research, Elsevier, vol. 282(1), pages 288-303.
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