Nowadays, with the rapid development of rail transportation systems, passenger demand and the possibility of the risks occurring in this industry have increased. These conditions cause uncertainty in passenger demand and the development of adverse impacts as a result of risks, which put the assurance of precise planning in jeopardy. To deal with uncertainty and lessen negative impacts, robust optimization of the train scheduling problem in the presence of risks is crucial.
View Article and Find Full Text PDFThis study assesses a multi-period capacitated maximal-covering location-allocation model for healthcare services, taking interservice referral as well as equity access into account. A two-stage optimization strategy is used to formulate the model. In the first stage, facilities are located to maximize covered demand, and in the second stage, patients are allocated to capacitated facilities based on their radius of coverage over multiple time periods.
View Article and Find Full Text PDFSustain Cities Soc
October 2021
The ongoing COVOD-19(SARS-CoV-2) outbreak has had a devastating impact on the economy, education and businesses. In this paper, the behavior of an epidemic is simulated on different contact networks. Herein, it is assumed that the infection may be transmitted at each contact from an infected person to a susceptible individual with a given probability.
View Article and Find Full Text PDFObjectives: This paper presents a reference data model for blood bank management to control blood inventories considering real-world uncertainties and constraints. It helps information systems identify blood product status for various critical decisions (such as replenishment, assignment, and issuing) instantly. Additionally, some significant optimization concepts of the inventory management literature for blood wastage and shortage reduction, such as clearance sale and substitution based on medical priorities, are applied in the model.
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