Heat Exchanger Networks
Conventional optimisation requires three problems to be formulated and solved to minimise the cost of designing a heat exchanger network. With the Engine, the formulation of a single NLP can be solved.
Octeract Engine found the best combination of assets by solving a multi-objective function, considering discontinuous constraints while building cardinality constraints automatically.
What is the best combination of item amounts and vendors to minimise the total cost of purchasing a required item, in bulk? The Engine manages to give an answer to this problem.
Case studies offer practical insight into the benefit of global optimisation. In a world where problems are non-linear, finding the best solution is complex. These case studies showcase how global optimisation can help.
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