Abstract: An aspect of the present invention relates to a computer-implemented method, the method comprising at least the steps of: obtaining, by a first computing device, sample location data, the sample location data comprising information indicative of a sample location of a biological sample; obtaining, by the first computing device, test data, the test data comprising information indicative of one or more clinical tests to be performed on the biological sample; selecting by evaluating laboratory data, by the first computing device, a processing laboratory from a first plurality of laboratories, wherein the processing laboratory is located at a processing laboratory location and the processing laboratory comprises one or more laboratory instruments, the one or more laboratory instruments being configured to carry out the one or more clinical tests to be performed on the biological sample; and instructing, by the first computing device, an agent to initiate a transfer of the biological sample from the sample locatio

Abstract: A computer-implemented method is provided.

Abstract: In a scenario where a laboratory is required to perform a plurality of tests on biological samples from a plurality of tubes in a manner that satisfies certain constraints, it is possible that the laboratory could handle the samples and assign them to machines in a manner which ensures that the relevant constraints are met. This could include using matrices and optimization functions to represent tubes, tests, machines and prescriptions, and could also include dynamically determining whether and how to aliquot the samples so as to meet the constraints given the conditions under which the samples would be processed.

Abstract: A method for solving the facility layout problem using a heuristic approach allows for multiple, highly efficient solutions to be automatically generated even when dealing with medium and large scale environments. Inputs to the method include a number of facilities each having a discipline and a dimension that must be placed in a laboratory area having a dimension and an entrance. The method sorts and begins to place facilities to generate a number of partial solutions, and each partial solution can be expanded until a final solution is reached or a termination criteria is satisfied. Expanded solutions that reach a final solution are reduced to a diverse set of solutions using a diversity measure. The reduced set of diverse solutions may then be improved upon using an optimization algorithm with less concern about efficiency.

Abstract: In a scenario where a laboratory is required to perform a plurality of tests on biological samples from a plurality of tubes in a manner that satisfies certain constraints, it is possible that the laboratory could handle the samples and assign them to machines in a manner which ensures that the relevant constraints are met. This could include using matrices and optimization functions to represent tubes, tests, machines and prescriptions, and could also include dynamically determining whether and how to aliquot the samples so as to meet the constraints given the conditions under which the samples would be processed.

Abstract: Laboratory instrument selection and the allocation of reagents to laboratory instruments may be optimized by using computer programs which minimize cost functions relative to various types of constraints. These constraints may include demand for tests, laboratory instrument operational capacity, laboratory instrument reagent capacity, and so on. In some embodiments, this optimization may combine reagent allocation with machine selection to aid in the selection of appropriate laboratory instruments.