A data-driven optimization framework for routing mobile medical facilities

We study the delivery of mobile medical services and in particular, the optimization of the joint stop location selection and routing of the mobile vehicles over a repetitive schedule consisting of multiple days. Considering the problem from the perspective of a mobile service provider company, we aim to provide the most revenue to the company by bringing the services closer to potential customers. Each customer location is associated with a score, which can be fully or partially covered based on the proximity of the mobile facility during the planning horizon. The problem is a variant of the team orienteering problem with prizes coming from covered scores. In addition to maximizing total covered score, a secondary criterion involves minimizing total travel distance/cost. We propose a data-driven optimization approach for this problem in which data analyses feed a mathematical programming model. We utilize a year-long transaction data originating from the customer banking activities of a major bank in Turkey. We analyze this dataset to first determine the potential service and customer locations in Istanbul by an unsupervised learning approach. We assign a score to each representative potential customer location based on the distances that the residents have taken for their past medical expenses. We set the coverage parameters by a spatial analysis. We formulate a mixed integer linear programming model and solve it to near-optimality using Cplex. We quantify the trade-off between capacity and service level. We also compare the results of several models differing in their coverage parameters to demonstrate the flexibility of our model and show the impact of accounting for full and partial coverage

Limestone dimension stone quarry waste properties for concrete in Western Turkey

The aim of this paper is to assess the influence of the composition and texture of the limestone on aggregate properties from the five working dimension stone quarries wastes of Karaburun Peninsula in Western Turkey. The limestone samples were tested to determine their petrographic, mineralogic, and chemical characteristics and aggregate properties. Then, the testing concretes were prepared by using these aggregates, and hardened concrete properties were determined. According to the results obtained, limestone was found to be suitable for use as coarse and fine aggregate in normal-strength concrete production. But, the quality of concretes made using the limestone aggregates were found to be dependent on the silica ratio present in them. The threshold value of the silica ratio is determined to be 2 % by weight for the alkali-silica reaction development in concrete made with the Karaburun dimension stone quarries wastes