389. Layout and location planning for automatic locker box systems under stochastic demand
Invited abstract in session TA-10: Logistics in the pandemic crisis, stream Logistics and Freight Transportation.
Thursday, 9:00-10:20Room: Schreckhorn
Authors (first author is the speaker)
| 1. | Michael Kahr
|
| Department of Statistics and Operations Research, University of Vienna | |
| 2. | Karl Doerner
|
| Department of Business Decisions and Analytics, University of Vienna | |
| 3. | Margaretha Gansterer
|
| University of Klagenfurt |
Abstract
The pandemic caused by the corona virus SARS-Cov-2 imposed many challenges to humanity. Besides health-care issues, a large increase in demand for home deliveries triggered by lockdowns and stay-at-home orders was observed. A potential gear to cushion such increased demand regards the mode of transport at the last mile. Appropriate transportation concepts during pandemics include performing last-mile delivery via (outdoor) automatic locker box systems where customers can collect their orderings 24/7 while ensuring social distancing. The location decision of such locker box systems is known to be crucial for their success. A challenging aspect regards uncertain customer demand for different commodities and therefore also deciding location-specific layouts of installed locker box systems. The latter challenges are addressed and the new stochastic multi-compartment locker location problem is proposed. The objective is to maximize the expected utility of the covered customer-demand given a budget an operator is willing to invest. An integer linear programming formulation is proposed together with an exact reformulation based on Benders decomposition. It is shown that each Benders cut can be separated in linear time. The proposed algorithms allow to solve large-scale instances to proven optimality in reasonable time. Besides computational results on artificial instances, a case study for Austria's capital Vienna is presented.
Keywords
- Mixed-Integer Programming
- Location
- Logistics
Status: accepted
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