Optimization of Strawberry Supply Chain from the Perspective of Producers

This thesis aims at maximizing the profit of a strawberry producer while satisfying the retailer's demand and meeting other constraints. The amount of strawberries to be delivered to the retailer signed in the contract is the main decision variable to be optimized in the problem. Furthermore, the transportation scheduling is also optimized to...

Prediction & optimization of alkali-activated concrete based on the random forest machine learning algorithm

Alkali-activated concrete (AAC) is regarded as a promising alternative construction material to reduce the CO₂ emission induced by Portland cement (PC) concrete. Due to the diversity in raw materials and complexity of reaction mechanisms, a commonly applied design code is still absent to date. This study attempts to directly...

Thermal Management of a Data Center White Space: A numerical study using computational fluid dynamics, flow & temperature predictions using neural networks, and white space design optimization using a genetic algorithm.

The total electrical energy consumption by all the operational data centers (located all over the world) is enormous (approx. 1% of the global electricity demand 20000TWh). This electrical energy is required 24x7 to operate and cool all the IT equipment present in the data center. The electrical energy required to cool all...

SMART mobility via prediction, optimization and personalization

In this chapter, we present a methodological approach for Smart Mobility that integrates three key features: prediction, optimization, and personalization. They are integrated in such a way that when a travel menu is offered, predicted conditions are considered in the attributes of alternatives and optimized system-level policies are maintained....

Multi-fidelity Co-Kriging Optimization using Hybrid Injected RANS and LES

The computation of complex turbulent flows design optimization processes is currently limited by the lack of accuracy of Reynolds-Averaged Navier-Stokes (RANS) in massively separated flows and the infeasible cost of multiple Large-Eddy Simulation (LES) evaluations. A novel method is presented, injecting data from LES or other high-fidelity...