Optimisation. 1. Bunge may at its sole discretion choose to offer a Grain Optimisation Product to Growers at any or all Bunge Facilities for specific Grain.
2. Any Optimisation Product offered by Bunge will be subject to the Product Rules in place at the time.
3. If the Warehouser chooses to Optimise its Grain, the Warehouser acknowledges and agrees that:
a. The Warehouser waives any right to transport, move or outturn it’s Grain by any other means than that authorized by Bunge.
b. The Warehouser will be bound by the Optimisation Product Rules.
c. The Warehouser has satisfied and complied with Bunge's Optimisation Rules.
x. Xxxxx may, at its sole discretion, provide the Warehouser with an Optimisation model; however it makes no representation or warranty as to the accuracy of any data and the model. The Warehouser acknowledges that it is responsible for the accuracy of the data and any model, including any price, recevial and Grain contract information.
x. Xxxxx will accept the Warehouser’s request and use its best endeavors’ to Optimise its Grain.
f. The Warehouser is responsible for any and all Optimisation decisions including (but limited to) the accuracy, suitability and correctness of any Grain and price data.
x. Xxxxx (including its officers, employees, contractors and agents) is not, and will not, offer the Warehouser any legal, tax, financial or accounting advice regarding the Optimisation or its suitability in general and /or to the Warehouser’s particular circumstances.
x. Xxxxx recommends that the Warehouser seek independent advice in making any Optimisation decision. The Warehouser acknowledges that Bunge has made this recommendation to the Warehouser.
i. The Warehouser will not seek nor solicit any advice or recommendation from Bunge (including its officers, employees, contractors and agents), and acknowledge that Bunge (including its officers, employees, contractors and agents) is not authorized to provide any advice or recommendation.
j. As a result of any Optimisation instructed by the Warehouser, that some or all of the Warehouser's Grain receivals will be adjusted to reflect the change in Grade required to achieve the Optimisation. This may include some Grain to be regarded to a lower quality grade, and some Grain to a higher quality grade. This will mean quality of Grain that the Warehouser is entitled to receive will change.
x. Xxxxx is not liable for any Loss, damage, cost or expense arising from or in relation to any Optimisation. Likewise, Bunge i...
Optimisation. TowerCo is entitled to optimise the TowerCo Infrastructure Network in order to offer a more efficient management, always ensuring the quality levels of the Services to be provided hereunder (“Optimisation”).
Optimisation. In order to provide the most definitive answers to the research questions, a number of optimisation studies were performed. These were designed to determine the most appropriate toxicity assays for the cell lines used in the project, to determine the ideal conditions for maximising the production of relevant data in these assays and to develop a relevant and reliable positive control for Western blotting of neuronal markers. Therefore, this chapter has been presented as a collection of individual studies containing related optimisation experiments.
Optimisation. An optimisation procedure may look very different depending on what is meant with the optimisation, and what the goal is. Common for all optimisation procedures are that different quantities are compared and either maximised or minimised to make the overall performance of the product better. The present optimisation procedure includes a sensitivity analysis to reduce the number of input parameters for the full-scale multi-objective optimisation procedure. The sensitivity analysis included in total 21 design parameters. They were distributed across the parameter space with a Latin Hypercube Sampling into 35 simulated design points. The sensitivity analysis was carried out at multiple operation points, and for both pump and turbine modes. Based on the results from the sensitivity analysis a narrower number of design parameters was chosen for the full multi objective optimisation procedure. The goal of the optimisation was to maximise the average power output of the turbine and minimise the power required for the pump, see section 1.3.1, and reduce the risk of cavitation. The latter is because it is important to reduce cavitation for fish mortality, and also extend the lifetime of the machine.
Optimisation. Consumption of services as defined in the following Standard GCloud offerings: Annex 1, 575902986439491-service-definition-document-2020-07-20-1153 Annex 2, 575902986439491-pricing-document-2020-07-20-1249 Invoiced Monthly in arrears.
1. Nina escalating to Live Chat / Messaging is counted as one Billing Session.
Optimisation. The challenge of identifying the more suitable path between the conflicting requirements of reducing greenhouse emissions and at the same time maintaining adequate safety of ships in adverse sea conditions is the main objective of the SHOPERA project. To this end, the development of multi-objective optimization procedures are foreseen in SHOPERA, in which a ship’s performance is assessed holistically, looking for the minimum powering requirement to ensure safe ship operation in adverse seaway/weather conditions, while keeping the right balance between ship economy, efficiency and safety of the ship and the marine/air environment. The planned optimization studies were implemented in two phases: The first phase consists of a Global Optimization, aiming to identify most favourable combinations of main dimensions, form parameters and other integrated characteristics of the ship, including powering and manoeuvring devices, for the selected operational profile. These studies should be carried out applying as far as possible simplified methods, developed within the project. The second phase consists of a Detailed Optimization, including hullform details. These studies should be carried out applying refined and more accurate methods.
