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? This is where it is provided by different vendors.
Case in Point
A case study offers great, practical insight into the tangible benefit of global optimisation. We live in a world where problems are non-linear and finding the best solution is complex. Case studies fearlessly tackle such problems head-on. Global optimisation is a game-changer. We’ve got the case studies to prove it.
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