— Data augmentation driven by optimization for membrane separation process synthesis
Artelys Knitro is used to design membrane gas separation processes with minimal separation costs.
— A temporal coherent topology optimization approach for assembly planning of bespoke frame structures
Find out how Artelys Knitro is being used in civil engineering research to optimise the planning of assembly sequences for frame structures, generating sequences that reduce intermediate deformations by 67%.
— A Reduced Variable Neighbourhood Search for the Beam Angle Optimisation Problem
Discover how Knitro has enabled solving the challenge of optimizing radiation dose distribution by defining the ideal configuration of beams, thereby ensuring the effective targeting of cancer cells while preserving healthy tissues.
— The use of Knitro's solver to evaluate and select the most efficient refrigerants for heat pumps
Discover how researchers use the nonlinear optimization solver Artelys Knitro to evaluate and select the most efficient refrigerants for heat pumps, in this article from the journal "Energy Technology".
— Minimal mass design of active tensegrity structures
The main challenge is to find the optimal balance between compression and tension constraints while minimizing system mass while ensuring structural integrity, resulting in reduced carbon impact structures.
— Molecule superstructures for computer-aided molecular and process design
Methods for predicting the properties of a molecular structure require finding the right trade-off between representation accuracy and computation time. Thanks to the application of Artelys Knitro to computer-aided molecular and process design, it is possible to represent all molecular structural information, enabling more accurate property predictions.
— The social cost of contacts: Theory and evidence for the first wave of the COVID-19 pandemic in Germany
Read how the nonlinear optimization solver Artelys Knitro helps researchers in epidemiology analyze the evolution of Covid-19 pandemic in Germany, in this article from “PLOS ONE”.
— A freight origin-destination synthesis model with mode choice
Find out how Artelys Knitro modeled and solved a non-linear, non-convex model to enable logistics managers to efficiently evaluate optimal multimodal freight flow scenarios.
— Buyer selection and service pricing in an electric fleet supply chain
This study focuses on the correct dimensioning of infrastructures in the determination of charging rates and the resolution of a mixed-integer nonlinear programming. The aim is to evaluate the impact of the combined parameters of the problem, and to describe a modeling framework and its managerial implications for taxicabs selection and pricing contracts.
— Optimal test and sensor selection for active fault diagnosis using integer programming
Find out how Artelys Knitro is used by control systems engineering researchers to select and design tests and sensors for optimal fault detection and isolation.
— Global supply chain pressures, international trade and inflation
Discover how Artelys Knitro addresses the challenges associated with measuring the distinct impacts of Covid-19 on various countries and economic sectors, as well as analyzing the persistent inflation generated by the pandemic while handling complementarity constraints within complex quantitative economic models.
— A horizontal collaborative approach for planning the wine grape harvesting
Find out how Artelys Knitro enables researchers to take into account numerous operational constraints related to harvesting in their modeling, in order to provide more equitable collaborative dispatching solutions.
— Learning to guide online multi-contact Receding Horizon Planning
Legged robots need to be able to plan their movements in real time in the event of environmental perturbations. Artelys Knitro enables trajectory optimisation problems to be solved so that the motion plan can be continuously updated.
— The effects of climate change in reindeer husbandry
See how Artelys Knitro helps researchers to understand the effects of climate change in reindeer husbandry in this article from “Ecological Applications”.
— On optimal buffer allocation for guaranteeing Quality of Service in multimedia internet broadcasting for mobile networks
Discover how the use of Artelys Knitro led to significant savings in the occupation of storage space on a telecommunications platform.
— Bound-constrained global optimization of functions with low effective dimensionality using multiple random embeddings
The challenges are to ensure convergence to the global optimum and to reduce problems to its effective subspace. The aim is to solve reduced sub-problems and identify global optimum solutions for neural network applications, complex engineering and physical simulations.
— Determining the reactive power range requirements for wind generators considering the correlation of electricity demand and wind generation
This study addresses the challenges of production due to meteorological variability, as well as maintaining voltage within operating standards, with an aim to solve the Optimal Power Flow model and identify reactive power range requirements.
— Matching of corroded defects in onshore pipelines based on In-Line Inspections and Voronoi partitions
The inspection of onshore pipelines can be subject to many uncertainties. In order to guarantee an adequate level of safety, an inspection schedule is defined and Artelys Knitro is used to determine the probabilities of detection and false alarm.
— Optimizing dynamic trajectories for robustness to disturbances using polytopic projections
Discover how Artelys Knitro has facilitated the dynamic trajectory of objects in complex environments by innovatively addressing challenges related to the violation of motion constraints and nonlinearities with its advanced algorithms in the article from “2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)”.
— Coordinated electric vehicle charging with reactive power support to distribution grids
In the face of challenges such as the coordination problem in recharging electric vehicles and energy losses, the achieved results include the successful integration of electric vehicles without impacting the network and the effective coordinated distribution of these vehicles.
— Optimal coordinated operation of distributed static series compensators for network congestion relief
Researchers in the energy sector are using Artelys Knitro to meet the challenges of integrating renewable energy sources and ensuring power grid security. The results of their efforts include reduced computing time and the implementation of near-optimal control actions.
— Harvesting selectivity and stochastic recruitment in economic models of age-structured fisheries
Read how researchers in fishery management use Artelys Knitro in this article from “Journal of Environmental Economics and Management”.
— Optimization of multistage membrane gas separation processes
The design of multistage membrane gas separation processes is a complex problem involving a variety of factors. Artelys Knitro helps to solve this problem through the development of an optimal design configuration and minimum separation costs.
— Large-scale optimization models used in the healthcare industry
Discover how Artelys Knitro and AMPL quickly enabled the planning of radiotherapy for cancer patients by integrating dosage constraints! The approach involves prioritizing clinical objectives to maximize tumor coverage with radiation while minimizing the impact on healthy tissues.
— Derivative-free optimization used in macro-economics
In macroeconomics, the series of DGSE (dynamic stochastic general equilibrium) models, which attempt to explain the effects of economic policies on economic growth. Discover how Artelys Knitro solved this highly linear problem, reducing computation time by a factor of 5, while maintaining the same objective function value.
— Optimize oil blending in a refinery
TotalEnergies owns and operates several refineries worldwide, producing millions of barrels per day by implementing complex refinery operations. In order to improve processes within its refineries, TotalEnergies wished to provide its planners with an operations management tool based on an optimization engine.
— Optimizing resource extraction
Orica delivers value by enabling mining operations to reduce the amount of waste they process, leading to increased sustainability, greater profitability and a smaller environmental footprint. The challenges include complex ore deposits and multiple processes resulting in industrial problem solving and increased productivity with a virtual mining chain integration.
— Energy optimisation of trajectories and coordination for cyclic multi-robot systems
Read how researchers in the automotive industry use Artelys Knitro in this article from “Robotics and Computer-Integrated Manufacturing”.
— Robust nonlinear mathematical transmission expansion planning based on German electricity market simulation
Read how experts use Artelys Knitro to solve the transmission expansion planning in this article from “Electric Power Systems Research”.
— Optimizing continuous cover and rotation forestry in mixed-species boreal forests
Read how researchers of the Economic-Ecological Research Group use Artelys Knitro in this article from “Canadian Journal of Forest Research".
— Hydrogen network optimization and hydrogenation reaction kinetics
Researchers in the oil and gas sector use Artelys Knitro to significantly decrease hydrogen usage while seamlessly integrating ecological and economic considerations. The outcomes are remarkable, with a 44% reduction in hydrogen consumption and a 38% decrease in environmental impact.
— A fuzzy hybrid integrated framework for portfolio optimization in private banking
In this article from "Expert Systems with Applications," financial services researchers delve into the use of Artelys Knitro for decision-making in complex and uncertain environments, aiming to select the optimal alternative. Results include portfolio optimization, enabling the identification of the best approach while considering regulatory concerns and investor objectives.
— Modeling and optimizing cone-joints for complex assemblies
Discover how Artelys Knitro enables the design of complex assemblable structures while ensuring their structural stability. The outcomes include optimized cone assembly and the resolution of complex models using the interior-point method.
— Robust Solutions to the Life-Cycle Consumption Problem
The life-cycle consumption problem consists in determining the best consumption pattern and investment decisions of individuals over their lifetime. Confronted with a high degree of uncertainty and the need to incorporate budgetary constraints, the results obtained include instances with a 30-year time horizon and improved outcomes, particularly in the most unfavorable scenarios.
— Tax policy models in Julia efficiently solved with Artelys Knitro
Economists work routinely with tax policy models formulated as inequality-constrained nonconvex optimization problems. They have a degeneracy feature: the number of active inequality constraints at a solution is typically several times larger than the number of variables in the problem, which makes them particularly difficult to solve.
— Optimizing sustainable electric power systems
Electric power systems are at the heart of the energy trilemma: affordability, sustainability and reliability. Powerful optimization software tools are required to plan electric power systems in order to achieve a twofold result: improving profitability of investments and ensuring reliable operating conditions. The challenges include the complexity of electrical systems such as the nonlinear energy flow equations and the large optimization problems. This results in the optimization of an electrical system with thousands of elements and sustainable electrical systems.
— How to achieve High speed landing of quadruped robots with Artelys Knitro
There are various and fascinating projects adopting Artelys Knitro. The MIT Biomimetic Robotics Lab used our nonlinear solver on quadruped robot. Artelys Knitro has been found to be the only non-linear solver capable of performing fast enough to be deployed onboard their robot for a real-time Optimal Landing Control.
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