2015
DOI: 10.1016/j.omega.2015.01.011
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A memetic algorithm for the patient transportation problem

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Cited by 77 publications
(50 citation statements)
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References 57 publications
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“…Litvak et al [3] introduced a mathematical method for computing the number of provincial beds for any given acknowledgment rate. In Z Zhang et al [4], for blocking likelihood, they figured the acclaimed Erlang loss formula:…”
Section: Review Of Literaturementioning
confidence: 99%
“…Litvak et al [3] introduced a mathematical method for computing the number of provincial beds for any given acknowledgment rate. In Z Zhang et al [4], for blocking likelihood, they figured the acclaimed Erlang loss formula:…”
Section: Review Of Literaturementioning
confidence: 99%
“…Equations (3)-(7) calculate the terms in the two objectives. Constraint (8) stipulates that delivery order i is picked up and transported after its production is completed. Constraints (9)-(10) guarantee that each delivery order is only picked up once.…”
Section: Mathematical Modelmentioning
confidence: 99%
“…It has been shown that the memetic algorithm could provide better optimum-seeking performance than GA over a wide variety of applications [8,9]. However, relatively little attention has been paid on using memetic algorithms to handle transportation scheduling problems.…”
Section: Introductionmentioning
confidence: 99%
“…Many variants of VRPs have been developed to tackle various constraints, such as Capacitated VRP (CVRP), VRP with Time Windows (VRPTW), Multiple Depot VRP (MDVRP) an so on [3]. The VRP not only plays an important role in industrial production but also gets widely applied to other areas [4], such as Supply Chain Logistics [5], Emergency Preparedness [6], Green Logistics [7] and Patient Transportation [8].…”
Section: Introductionmentioning
confidence: 99%