Main new features
This new version makes it easier to solve job-shop problems (JSP). Artelys Kalis improves the modeling and resolution of optimization problems in IT and operations research where jobs have to be scheduled and assigned to resources .
On the modelling side, the user is now able to define a set-up time between two tasks requiring the same resource. For example, it is now easy to model a scheduling problem where the maintenance tasks are to be performed in different places meaning the skilled technicians required for these tasks must travel between these places.
On the resolution side, the Timetable algorithm, used for the propagation of the resource constraints for the tasks, has been vastly improved, notably for the alternative resources. As a result, the performance of Artelys Kalis has vastly improved. For example, in the case of a scheduling problem with up to 250 alternative resources as a function of the number of tasks planned, the computation time reduces as shown below:
Other new features of Artelys Kalis 12.8:
Support of Python 3 Cross-platform random numbers generation
For more information, do not hesitate to contact us.
— Join Artelys on May 18th to learn more about Artelys Knitro, the most advanced solver for nonlinear optimization and ways to unleash the full potential of mathematical optimization.
— Artelys is thrilled to invite you to the METIS 2 Dissemination Event on May 31th. During this online event, we will present the METIS project’s latest results and discuss the benefits of using this modeling tool for energy and climate policymaking.
— As part of the METIS project, Artelys delivered a first model in 2018 to the European Commission. This year, Artelys has provided a major upgrade of the energy system model METIS.
Release of ADEME’s report “Modeling and optimizing French and European power mixes from 2020 to 2060”
— ADEME, the French energy and environment agency, contracted with Artelys to analyze four power systems scenarios.
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