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Evaluation of an Exclusive Spur Dike U-Turn Design with Radar-Collected Data and Simulation
Published on: February 1, 2020
Real operational data for the concrete delivery problem
Alexandros Tzanetos1, Maude Blondin1
1Multiobjective Optimization REsearch Lab (MORE Lab), Department of Electrical Engineering & Computer Engineering, Faculty of Engineering, Université de Sherbrooke, 2500, boulevard de l'Université Sherbrooke, Sherbrooke, J1K 2R1, Quebec, Canada.
Abstract:
The data article describes a real operational dataset for the Concrete Delivery Problem (CDP). The dataset consists of 263 instances corresponding to daily orders of concrete from construction sites in Quebec, Canada. A concrete producer, i.e., a concrete-producing company that delivers concrete, provided the raw data. We cleaned the data by removing entries corresponding to non-complete orders. We processed these raw data to form instances useful for benchmarking optimization algorithms developed to solve the CDP. We also anonymized the published dataset by removing any client information and addresses corresponding to production or construction sites. The dataset is useful for researchers and practitioners studying the CDP. It can be processed to create artificial data for variations of the CDP. In its current form, the data contain information about intra-day orders. Thus, selected instances from the dataset are useful for CDP's dynamic aspect considering real-time orders.
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