Sökning: "flow routing"
Visar resultat 1 - 5 av 54 uppsatser innehållade orden flow routing.
1. Improving network performance with a polarization-aware routing approach
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Traffic polarization in networks refers to the phenomenon where traffic tends to concentrate along specific routes or edges when doing multipath routing, leading to imbalanced flow patterns. This spatial distribution of traffic can result in congested and overburdened links, while other routes remain underutilized. LÄS MER
2. Optimal Multi-Commodity Network Flow of Electric Vehicles with Charge Constraints
Kandidat-uppsats, KTH/Skolan för teknikvetenskap (SCI)Sammanfattning : The focus of this thesis is to find, visualize and analyze the optimal flow of autonomous electric vehicles with charge constraints in urban traffic with respect to energy consumption. The traffic has been formulated as a static multi-commodity network flow problem, for which two different models have been implemented to handle the charge constraints. LÄS MER
3. The Impact of Demand Patterns and Pathfinding Strategies on Payment Channel Networks
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Payment Channel Networks (PCNs) provide a solution to the scalability problem in blockchain technology. They facilitate multiple-hop transactions via payment channels between peers, allowing for the execution of several transactions before updating each node’s balance on the blockchain. LÄS MER
4. Standardisering som grund till utveckling av enstycksflöde
Kandidat-uppsats, Högskolan i Skövde/Institutionen för ingenjörsvetenskapSammanfattning : Nimoverken is the world's largest producer of drying cabinets, located in Hova, Sweden. Drying cabinets are sold mainly in the Nordic countries and to a lesser degree to USA, England and South Korea, where drying cabinets are an increasing niche product on the market. LÄS MER
5. Deep Reinforcement Learning and Simulation for the Optimization of Production Systems
Master-uppsats, Uppsala universitet/Institutionen för informationsteknologiSammanfattning : The main objective of this master thesis project is to use the deep reinforcement learning (DRL) and simulation method for optimization of production systems. In this project, the Deep Q-learning Networks (DQN) algorithm is first used to optimize seven decision variables in Averill Law’s production system to find the best profit, with 99. LÄS MER