Sökning: "Vehicle Scheduling"
Visar resultat 1 - 5 av 41 uppsatser innehållade orden Vehicle Scheduling.
1. Holistic embedding of equivalent conicity in wheelset maintenance
Master-uppsats, KTH/Väg- och spårfordon samt konceptuell fordonsdesignSammanfattning : With continuing digitization of railways an increasing number of data is recorded but particularly in operation advanced analysis tends to be partially rudimentary. Yet, it is essential to implement sophisticated processing for all records in order to develop more purposeful and predictive vehicle maintenance strategies that adhere to the increasing requirements imposed by the homologation. LÄS MER
2. When is Electric Freight Cost Competitive? : Computational modeling and simulation of total cost of ownership for electric truck fleets
Uppsats för yrkesexamina på avancerad nivå, Linköpings universitet/Institutionen för ekonomisk och industriell utvecklingSammanfattning : Battery electric trucks (BETs) offer environmental benefits in terms of reduced carbon emissions and enhanced energy efficiency but have been challenged with economic viability compared to conventional internal combustion engine trucks (ICETs) caused by substantial acquisition costs, limited charging infrastructure, and concerns regarding range and payload capacity. Previous studies focus on TCO at the vehicle or policy level but overlook the system and firm-level impacts. LÄS MER
3. Randomized heuristic scheduling of electrical distribution network maintenance in spatially clustered balanced zones
Master-uppsats, KTH/GeoinformatikSammanfattning : Reliable electricity distribution systems are crucial; hence, the maintenance of such systems is highly important, and in Sweden strictly regulated. Poorly planned maintenance scheduling leads unnecessary driving which contributes to increased emissions and costs. LÄS MER
4. 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
5. Smart Charging and Ancillary Services in the Malmö region
Uppsats för yrkesexamina på avancerad nivå, Lunds universitet/Industriell elektroteknik och automationSammanfattning : To meet Sweden’s national environmental goal of 70% emissions reduction by 2030 compared to 2010 from domestic transport, electrification is considered key. However, as more chargeable vehicles are integrated into the market, shortage of capacity for charging infrastructure may arise. LÄS MER